
R version 2.11.1 (2010-05-31)
Copyright (C) 2010 The R Foundation for Statistical Computing
ISBN 3-900051-07-0

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> source("pscore_estimation_core1.R")
Loading required package: gbm
Loading required package: survival
Loading required package: splines
Loading required package: lattice
Loaded gbm 1.6-3.1 
Loading required package: survey

Attaching package: 'survey'

The following object(s) are masked from 'package:graphics':

    dotchart

Loading required package: xtable
Loading required package: MASS
Loading required package: mlbench
Loading required package: nnet
Loading required package: class

Attaching package: 'ipred'

The following object(s) are masked from 'package:survey':

    cv

randomForest 4.5-36
Type rfNews() to see new features/changes/bug fixes.
> library(Matching)
Loading required package: rgenoud
##  rgenoud (Version 5.6-7, Build Date: 2010-06-01)
##  See http://sekhon.berkeley.edu/rgenoud for additional documentation.
## 
##  Matching (Version 4.7-10, Build Date: 2010/08/13)
##  See http://sekhon.berkeley.edu/matching for additional documentation.
##  Please cite software as:
##   Jasjeet S. Sekhon. Forthcoming. ``Multivariate and Propensity Score Matching
##   Software with Automated Balance Optimization: The Matching package for R.''
##   Journal of Statistical Software. 
##
> 
> options(warn=1)
> 
> load(file="RData.simdata.D.obs1000.reps1000")
> dta <- simdata.D.obs1000.reps1000
> rm(simdata.D.obs1000.reps1000)
> gc()
           used (Mb) gc trigger  (Mb) max used (Mb)
Ncells   200676 10.8     407500  21.8   350000 18.7
Vcells 12195008 93.1   13300699 101.5 12195652 93.1
> 
> #true estimate
> g1 <- -0.4
> 
> sims <- dim(dta)[2]
> nobs <- length(dta[1,2]$w1)
> 
> true.est <- matrix(0, nrow=sims, ncol=1)
> 
> logit.pscore <- list()
> logit.est <- matrix(0, nrow=sims, ncol=1)
> logit.nSE <- matrix(0, nrow=sims, ncol=1)
> logit.aiSE <- matrix(0, nrow=sims, ncol=1)
> 
> boosting.pscore <- list()
> boosting.desc <- list()
> boosting.est <- matrix(0, nrow=sims, ncol=1)
> boosting.nSE <- matrix(0, nrow=sims, ncol=1)
> boosting.aiSE <- matrix(0, nrow=sims, ncol=1)
> 
> forest.pscore <- list()
> forest.est <- matrix(0, nrow=sims, ncol=1)
> forest.nSE <- matrix(0, nrow=sims, ncol=1)
> forest.aiSE <- matrix(0, nrow=sims, ncol=1)
> 
> nnet.pscore <- list()
> nnet.est <- matrix(0, nrow=sims, ncol=1)
> nnet.nSE <- matrix(0, nrow=sims, ncol=1)
> nnet.aiSE <- matrix(0, nrow=sims, ncol=1)
> 
> count <- 0
> for (s in 1:sims)
+   {
+     cat("\n\ns:",s,"\n")
+     count <- count+1
+ 
+     sdta <- as.data.frame(dta[,s])
+ 
+     #true model
+ #    lm1 <- lm(y.a~ z.a+ w1 + w2 + w3 + w4 + w8 + w9 + w10, data=sdta)
+ #    true.est[s] <- lm1$coef[2]
+ #    cat("truth:",mean(true.est[1:s]),"\n")
+ 
+     #logit
+     logit.ps <- glm(z.a ~ w1+w2+w3+w4+w5+w6+w7+w8+w9+w10, data=sdta, family=binomial(link="logit"))$fitted
+     logit.pscore[[s]] <- logit.ps
+     m1 <- Match(Y=sdta$y.a, Tr=sdta$z.a, X=logit.ps, estimand="ATT", M=1)
+     logit.est[s] <-  m1$est
+     logit.nSE[s] <- m1$se.standard
+     logit.aiSE[s] <- m1$se
+ 
+     cat("logit",s,":",m1$est,"\n")
+     if(s>1)
+       {
+         cat("logit mean",s,":",mean(logit.est[1:s]),"\n")
+         rmse <- sqrt(mean((logit.est[1:s]-g1)^2))
+         cat("logit RMSE",s,":",rmse,"\n")
+       }
+ 
+     #boosting!
+     ps.model <- ps(z.a ~ w1+w2+w3+w4+w5+w6+w7+w8+w9+w10,
+                    data=sdta, title="none", stop.method=stop.methods["ks.stat.mean"],
+                    plots="none", pdf.plots=F, n.trees=20000, interaction.depth=4,
+                    shrinkage=0.0005, verbose=FALSE)
+ 
+     boosting.pscore[[s]] <- ps.model$ps
+     boosting.desc[[s]] <- ps.model$desc
+ 
+     m1 <- Match(Y=sdta$y.a, Tr=sdta$z.a, X=ps.model$ps, estimand="ATT", M=1)
+     boosting.est[s] <-  m1$est
+     boosting.nSE[s] <- m1$se.standard
+     boosting.aiSE[s] <- m1$se
+ 
+     cat("\nboosting",s,":",m1$est,"\n")
+     if(s>1)
+       {
+         cat("boosting mean",s,":",mean(boosting.est[1:s]),"\n")
+         rmse <- sqrt(mean((boosting.est[1:s]-g1)^2))
+         cat("boosting RMSE",s,":",rmse,"\n")
+       }    
+ 
+ 
+     #Random Forest
+     ps1 <- 1
+     while (max(ps1)> .999) {
+ #      gc(verbose=TRUE)
+       fps.model <- randomForest(as.factor(z.a) ~ w1+w2+w3+w4+w5+w6+w7+w8+w9+w10, data=sdta)
+       ps1 <- fps.model$votes[, 2]
+     }
+     
+     forest.pscore[[s]] <- ps1
+ 
+     m1 <- Match(Y=sdta$y.a, Tr=sdta$z.a, X=ps1, estimand="ATT", M=1)
+     forest.est[s] <-  m1$est
+     forest.nSE[s] <- m1$se.standard
+     forest.aiSE[s] <- m1$se
+ 
+     cat("\nforest",s,":",m1$est,"\n")
+     if(s>1)
+       {
+         cat("forest mean",s,":",mean(forest.est[1:s]),"\n")
+         rmse <- sqrt(mean((forest.est[1:s]-g1)^2))
+         cat("forest RMSE",s,":",rmse,"\n")
+       }
+ 
+     n1 <- nnet(z.a ~ w1+w2+w3+w4+w5+w6+w7+w8+w9+w10, size=40, data=sdta, trace=FALSE)
+     nnet.pscore[[s]] <- n1$fitted.values
+ 
+     m1 <- Match(Y=sdta$y.a, Tr=sdta$z.a, X=n1$fitted.values, estimand="ATT", M=1)
+     nnet.est[s] <-  m1$est
+     nnet.nSE[s] <- m1$se.standard
+     nnet.aiSE[s] <- m1$se
+ 
+     cat("\nnnet",s,":",m1$est,"\n")
+     if(s>1)
+       {
+         cat("nnet mean",s,":",mean(nnet.est[1:s]),"\n")
+         rmse <- sqrt(mean((nnet.est[1:s]-g1)^2))
+         cat("nnet RMSE",s,":",rmse,"\n")
+       }    
+ 
+     if (count>50)
+       {
+         save.image("RData.sims.D.nobs1000")
+         count <- 0
+       }
+   }#end of sims loop


s: 1 
logit 1 : -0.4507588 

boosting 1 : -0.5567563 

forest 1 : -0.4477211 

nnet 1 : -0.5765604 


s: 2 
logit 2 : -0.4396137 
logit mean 2 : -0.4451863 
logit RMSE 2 : 0.04552859 

boosting 2 : -0.7099728 
boosting mean 2 : -0.6333645 
boosting RMSE 2 : 0.2456172 

forest 2 : -0.4069065 
forest mean 2 : -0.4273138 
forest RMSE 2 : 0.0340955 

nnet 2 : -0.2662749 
nnet mean 2 : -0.4214176 
nnet RMSE 2 : 0.1566141 


s: 3 
logit 3 : -0.4101048 
logit mean 3 : -0.4334924 
logit RMSE 3 : 0.03762894 

boosting 3 : -0.4002861 
boosting mean 3 : -0.5556717 
boosting RMSE 3 : 0.2005457 

forest 3 : -0.3795383 
forest mean 3 : -0.4113886 
forest RMSE 3 : 0.03024173 

nnet 3 : -0.5768731 
nnet mean 3 : -0.4732361 
nnet RMSE 3 : 0.1636460 


s: 4 
logit 4 : -0.4339318 
logit mean 4 : -0.4336023 
logit RMSE 4 : 0.03673956 

boosting 4 : -0.3689035 
boosting mean 4 : -0.5089797 
boosting RMSE 4 : 0.1743723 

forest 4 : -0.3423381 
forest mean 4 : -0.394126 
forest RMSE 4 : 0.03895057 

nnet 4 : -0.3674243 
nnet mean 4 : -0.4467832 
nnet RMSE 4 : 0.1426545 


s: 5 
logit 5 : -0.4491699 
logit mean 5 : -0.4367158 
logit RMSE 5 : 0.0395395 

boosting 5 : -0.4652327 
boosting mean 5 : -0.5002303 
boosting RMSE 5 : 0.1586682 

forest 5 : -0.3775173 
forest mean 5 : -0.3908043 
forest RMSE 5 : 0.03626033 

nnet 5 : -0.4224937 
nnet mean 5 : -0.4419253 
nnet RMSE 5 : 0.12799 


s: 6 
logit 6 : -0.4124984 
logit mean 6 : -0.4326796 
logit RMSE 6 : 0.03645332 

boosting 6 : -0.1695343 
boosting mean 6 : -0.4451143 
boosting RMSE 6 : 0.1727197 

forest 6 : -0.2613551 
forest mean 6 : -0.3692294 
forest RMSE 6 : 0.0655699 

nnet 6 : -0.4175726 
nnet mean 6 : -0.4378665 
nnet RMSE 6 : 0.1170584 


s: 7 
logit 7 : -0.4177887 
logit mean 7 : -0.4305523 
logit RMSE 7 : 0.03441243 

boosting 7 : -0.4748267 
boosting mean 7 : -0.4493589 
boosting RMSE 7 : 0.1623891 

forest 7 : -0.3395509 
forest mean 7 : -0.3649896 
forest RMSE 7 : 0.06486311 

nnet 7 : -0.3626064 
nnet mean 7 : -0.4271151 
nnet RMSE 7 : 0.1092927 


s: 8 
logit 8 : -0.4953181 
logit mean 8 : -0.438648 
logit RMSE 8 : 0.04660344 

boosting 8 : -0.4127296 
boosting mean 8 : -0.4447803 
boosting RMSE 8 : 0.1519677 

forest 8 : -0.338906 
forest mean 8 : -0.3617292 
forest RMSE 8 : 0.06440403 

nnet 8 : -0.1389827 
nnet mean 8 : -0.3910985 
nnet RMSE 8 : 0.1377245 


s: 9 
logit 9 : -0.4133946 
logit mean 9 : -0.4358421 
logit RMSE 9 : 0.04416442 

boosting 9 : -0.3642239 
boosting mean 9 : -0.4358296 
boosting RMSE 9 : 0.143772 

forest 9 : -0.3362764 
forest mean 9 : -0.3589011 
forest RMSE 9 : 0.06432879 

nnet 9 : -0.2964377 
nnet mean 9 : -0.3805806 
nnet RMSE 9 : 0.1343583 


s: 10 
logit 10 : -0.3295936 
logit mean 10 : -0.4252172 
logit RMSE 10 : 0.0474463 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 10 : -0.5369765 
boosting mean 10 : -0.4459443 
boosting RMSE 10 : 0.1431070 

forest 10 : -0.3578605 
forest mean 10 : -0.358797 
forest RMSE 10 : 0.06246557 

nnet 10 : -0.6681962 
nnet mean 10 : -0.4093422 
nnet RMSE 10 : 0.1531008 


s: 11 
logit 11 : -0.4094431 
logit mean 11 : -0.4237832 
logit RMSE 11 : 0.04532779 

boosting 11 : -0.4544242 
boosting mean 11 : -0.4467152 
boosting RMSE 11 : 0.1374303 

forest 11 : -0.4300707 
forest mean 11 : -0.3652764 
forest RMSE 11 : 0.06024474 

nnet 11 : -0.3879845 
nnet mean 11 : -0.4074006 
nnet RMSE 11 : 0.1460209 


s: 12 
logit 12 : -0.4337502 
logit mean 12 : -0.4246138 
logit RMSE 12 : 0.04447824 

boosting 12 : -0.366211 
boosting mean 12 : -0.4400065 
boosting RMSE 12 : 0.1319406 

forest 12 : -0.3447444 
forest mean 12 : -0.3635654 
forest RMSE 12 : 0.05984487 

nnet 12 : -0.3663502 
nnet mean 12 : -0.4039797 
nnet RMSE 12 : 0.1401414 


s: 13 
logit 13 : -0.5174275 
logit mean 13 : -0.4317533 
logit RMSE 13 : 0.05372937 

boosting 13 : -0.4524026 
boosting mean 13 : -0.44096 
boosting RMSE 13 : 0.1275948 

forest 13 : -0.3788408 
forest mean 13 : -0.3647405 
forest RMSE 13 : 0.0577958 

nnet 13 : -0.5118391 
nnet mean 13 : -0.4122766 
nnet RMSE 13 : 0.1381703 


s: 14 
logit 14 : -0.572044 
logit mean 14 : -0.4417741 
logit RMSE 14 : 0.06924497 

boosting 14 : -0.6335347 
boosting mean 14 : -0.4547154 
boosting RMSE 14 : 0.1378882 

forest 14 : -0.4868937 
forest mean 14 : -0.3734657 
forest RMSE 14 : 0.06034136 

nnet 14 : -0.5094029 
nnet mean 14 : -0.4192142 
nnet RMSE 14 : 0.1363169 


s: 15 
logit 15 : -0.4312427 
logit mean 15 : -0.441072 
logit RMSE 15 : 0.06738161 

boosting 15 : -0.502498 
boosting mean 15 : -0.4579009 
boosting RMSE 15 : 0.1358161 

forest 15 : -0.4027093 
forest mean 15 : -0.3754153 
forest RMSE 15 : 0.05829949 

nnet 15 : -0.2633072 
nnet mean 15 : -0.4088204 
nnet RMSE 15 : 0.1363420 


s: 16 
logit 16 : -0.521303 
logit mean 16 : -0.4460864 
logit RMSE 16 : 0.07194557 

boosting 16 : -0.902028 
boosting mean 16 : -0.4856588 
boosting RMSE 16 : 0.1817832 

forest 16 : -0.3395769 
forest mean 16 : -0.3731754 
forest RMSE 16 : 0.05843448 

nnet 16 : -0.5243095 
nnet mean 16 : -0.4160385 
nnet RMSE 16 : 0.1356213 


s: 17 
logit 17 : -0.4582741 
logit mean 17 : -0.4468034 
logit RMSE 17 : 0.07121406 

boosting 17 : -0.4115851 
boosting mean 17 : -0.4813015 
boosting RMSE 17 : 0.176378 

forest 17 : -0.4296076 
forest mean 17 : -0.3764949 
forest RMSE 17 : 0.05714276 

nnet 17 : -0.4931288 
nnet mean 17 : -0.4205732 
nnet RMSE 17 : 0.1334966 


s: 18 
logit 18 : -0.4086599 
logit mean 18 : -0.4446843 
logit RMSE 18 : 0.06923772 

boosting 18 : -0.5407142 
boosting mean 18 : -0.4846022 
boosting RMSE 18 : 0.1745879 

forest 18 : -0.4593335 
forest mean 18 : -0.3810971 
forest RMSE 18 : 0.05726667 

nnet 18 : -0.5057883 
nnet mean 18 : -0.4253074 
nnet RMSE 18 : 0.1321098 


s: 19 
logit 19 : -0.3946791 
logit mean 19 : -0.4420524 
logit RMSE 19 : 0.0674021 

boosting 19 : -0.5633797 
boosting mean 19 : -0.4887484 
boosting RMSE 19 : 0.174016 

forest 19 : -0.2765676 
forest mean 19 : -0.3755955 
forest RMSE 19 : 0.06251991 

nnet 19 : -0.4611815 
nnet mean 19 : -0.4271955 
nnet RMSE 19 : 0.1293501 


s: 20 
logit 20 : -0.3742088 
logit mean 20 : -0.4386602 
logit RMSE 20 : 0.06594809 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 20 : -0.4429282 
boosting mean 20 : -0.4864574 
boosting RMSE 20 : 0.1698812 

forest 20 : -0.3742136 
forest mean 20 : -0.3755264 
forest RMSE 20 : 0.06120907 

nnet 20 : -0.1052475 
nnet mean 20 : -0.4110981 
nnet RMSE 20 : 0.1422632 


s: 21 
logit 21 : -0.3056034 
logit mean 21 : -0.4323242 
logit RMSE 21 : 0.0675749 

boosting 21 : -0.3815535 
boosting mean 21 : -0.481462 
boosting RMSE 21 : 0.1658360 

forest 21 : -0.2960198 
forest mean 21 : -0.3717404 
forest RMSE 21 : 0.06389831 

nnet 21 : -0.3876578 
nnet mean 21 : -0.4099819 
nnet RMSE 21 : 0.1388608 


s: 22 
logit 22 : -0.4697162 
logit mean 22 : -0.4340238 
logit RMSE 22 : 0.0676737 

boosting 22 : -0.6632202 
boosting mean 22 : -0.4897237 
boosting RMSE 22 : 0.1714666 

forest 22 : -0.3322324 
forest mean 22 : -0.3699446 
forest RMSE 22 : 0.06407926 

nnet 22 : -0.4083459 
nnet mean 22 : -0.4099075 
nnet RMSE 22 : 0.1356798 


s: 23 
logit 23 : -0.4413968 
logit mean 23 : -0.4343444 
logit RMSE 23 : 0.06674669 

boosting 23 : -0.5599748 
boosting mean 23 : -0.4927781 
boosting RMSE 23 : 0.1709831 

forest 23 : -0.4383884 
forest mean 23 : -0.3729204 
forest RMSE 23 : 0.06317987 

nnet 23 : -0.4949127 
nnet mean 23 : -0.4136034 
nnet RMSE 23 : 0.1341652 


s: 24 
logit 24 : -0.5572042 
logit mean 24 : -0.4394636 
logit RMSE 24 : 0.07279564 

boosting 24 : -0.7621133 
boosting mean 24 : -0.5040004 
boosting RMSE 24 : 0.1829772 

forest 24 : -0.4227098 
forest mean 24 : -0.3749949 
forest RMSE 24 : 0.06202309 

nnet 24 : -0.5455206 
nnet mean 24 : -0.4190999 
nnet RMSE 24 : 0.1346574 


s: 25 
logit 25 : -0.4876936 
logit mean 25 : -0.4413928 
logit RMSE 25 : 0.0734496 

boosting 25 : -0.6595923 
boosting mean 25 : -0.5102241 
boosting RMSE 25 : 0.1866466 

forest 25 : -0.3998431 
forest mean 25 : -0.3759889 
forest RMSE 25 : 0.06076998 

nnet 25 : -0.4886956 
nnet mean 25 : -0.4218838 
nnet RMSE 25 : 0.133124 


s: 26 
logit 26 : -0.360605 
logit mean 26 : -0.4382855 
logit RMSE 26 : 0.07243646 

boosting 26 : -0.3649899 
boosting mean 26 : -0.5046382 
boosting RMSE 26 : 0.1831508 

forest 26 : -0.3297827 
forest mean 26 : -0.3742117 
forest RMSE 26 : 0.06116033 

nnet 26 : -0.5407213 
nnet mean 26 : -0.4264544 
nnet RMSE 26 : 0.1334242 


s: 27 
logit 27 : -0.4963904 
logit mean 27 : -0.4404376 
logit RMSE 27 : 0.07346306 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 27 : -0.5621803 
boosting mean 27 : -0.5067694 
boosting RMSE 27 : 0.1824171 

forest 27 : -0.4311314 
forest mean 27 : -0.3763198 
forest RMSE 27 : 0.06031534 

nnet 27 : -0.5028017 
nnet mean 27 : -0.4292821 
nnet RMSE 27 : 0.1324164 


s: 28 
logit 28 : -0.373346 
logit mean 28 : -0.4380414 
logit RMSE 28 : 0.07231494 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 28 : -0.6865425 
boosting mean 28 : -0.5131898 
boosting RMSE 28 : 0.1871362 

forest 28 : -0.2956334 
forest mean 28 : -0.3734382 
forest RMSE 28 : 0.06242618 

nnet 28 : -0.4296848 
nnet mean 28 : -0.4292965 
nnet RMSE 28 : 0.1301513 


s: 29 
logit 29 : -0.4954528 
logit mean 29 : -0.4400211 
logit RMSE 29 : 0.07323459 

boosting 29 : -0.6215278 
boosting mean 29 : -0.5169256 
boosting RMSE 29 : 0.1884266 

forest 29 : -0.3778662 
forest mean 29 : -0.3735909 
forest RMSE 29 : 0.06147797 

nnet 29 : -0.3331443 
nnet mean 29 : -0.4259809 
nnet RMSE 29 : 0.1284888 


s: 30 
logit 30 : -0.4888108 
logit mean 30 : -0.4416475 
logit RMSE 30 : 0.07380677 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 30 : -0.2972977 
boosting mean 30 : -0.5096047 
boosting RMSE 30 : 0.1862061 

forest 30 : -0.3714609 
forest mean 30 : -0.3735199 
forest RMSE 30 : 0.06066882 

nnet 30 : -0.7664529 
nnet mean 30 : -0.43733 
nnet RMSE 30 : 0.1429521 


s: 31 
logit 31 : -0.5171612 
logit mean 31 : -0.4440834 
logit RMSE 31 : 0.0755944 

boosting 31 : -0.5026014 
boosting mean 31 : -0.5093788 
boosting RMSE 31 : 0.1841027 

forest 31 : -0.3431641 
forest mean 31 : -0.3725407 
forest RMSE 31 : 0.06054896 

nnet 31 : -0.4213991 
nnet mean 31 : -0.4368161 
nnet RMSE 31 : 0.1406801 


s: 32 
logit 32 : -0.4285032 
logit mean 32 : -0.4435965 
logit RMSE 32 : 0.07457429 

boosting 32 : -0.4876334 
boosting mean 32 : -0.5086992 
boosting RMSE 32 : 0.1818643 

forest 32 : -0.3732947 
forest mean 32 : -0.3725642 
forest RMSE 32 : 0.05978207 

nnet 32 : -0.3471297 
nnet mean 32 : -0.4340134 
nnet RMSE 32 : 0.1387796 


s: 33 
logit 33 : -0.3650994 
logit mean 33 : -0.4412178 
logit RMSE 33 : 0.07368657 

boosting 33 : -0.3841594 
boosting mean 33 : -0.5049253 
boosting RMSE 33 : 0.1791088 

forest 33 : -0.3690608 
forest mean 33 : -0.3724581 
forest RMSE 33 : 0.05911516 

nnet 33 : -0.2268423 
nnet mean 33 : -0.4277355 
nnet RMSE 33 : 0.1399454 


s: 34 
logit 34 : -0.4108966 
logit mean 34 : -0.440326 
logit RMSE 34 : 0.0726189 

boosting 34 : -0.5396983 
boosting mean 34 : -0.505948 
boosting RMSE 34 : 0.1780742 

forest 34 : -0.372038 
forest mean 34 : -0.3724457 
forest RMSE 34 : 0.05843643 

nnet 34 : -0.2744406 
nnet mean 34 : -0.4232268 
nnet RMSE 34 : 0.1395435 


s: 35 
logit 35 : -0.4224973 
logit mean 35 : -0.4398166 
logit RMSE 35 : 0.07167492 

boosting 35 : -0.556619 
boosting mean 35 : -0.5073958 
boosting RMSE 35 : 0.1774972 

forest 35 : -0.4805143 
forest mean 35 : -0.3755334 
forest RMSE 35 : 0.05918164 

nnet 35 : -0.6419947 
nnet mean 35 : -0.4294773 
nnet RMSE 35 : 0.1434894 


s: 36 
logit 36 : -0.3337106 
logit mean 36 : -0.4368692 
logit RMSE 36 : 0.0715308 

boosting 36 : -0.4174047 
boosting mean 36 : -0.504896 
boosting RMSE 36 : 0.1750386 

forest 36 : -0.4146267 
forest mean 36 : -0.3766193 
forest RMSE 36 : 0.05840478 

nnet 36 : -0.4729303 
nnet mean 36 : -0.4306843 
nnet RMSE 36 : 0.1420037 


s: 37 
logit 37 : -0.3072152 
logit mean 37 : -0.4333651 
logit RMSE 37 : 0.07218756 

boosting 37 : -0.2614867 
boosting mean 37 : -0.4983174 
boosting RMSE 37 : 0.1741522 

forest 37 : -0.2690847 
forest mean 37 : -0.3737130 
forest RMSE 37 : 0.06149908 

nnet 37 : -0.3873975 
nnet mean 37 : -0.4295144 
nnet RMSE 37 : 0.1400869 


s: 38 
logit 38 : -0.5033019 
logit mean 38 : -0.4352055 
logit RMSE 38 : 0.07317605 

boosting 38 : -0.2493484 
boosting mean 38 : -0.4917656 
boosting RMSE 38 : 0.1735745 

forest 38 : -0.3612611 
forest mean 38 : -0.3733853 
forest RMSE 38 : 0.06100901 

nnet 38 : -0.4128981 
nnet mean 38 : -0.4290771 
nnet RMSE 38 : 0.1382472 


s: 39 
logit 39 : -0.3891694 
logit mean 39 : -0.4340251 
logit RMSE 39 : 0.07225262 

boosting 39 : -0.4402626 
boosting mean 39 : -0.490445 
boosting RMSE 39 : 0.1714560 

forest 39 : -0.301885 
forest mean 39 : -0.3715519 
forest RMSE 39 : 0.06223741 

nnet 39 : -0.3202981 
nnet mean 39 : -0.4262879 
nnet RMSE 39 : 0.1370588 


s: 40 
logit 40 : -0.3545738 
logit mean 40 : -0.4320388 
logit RMSE 40 : 0.07170438 

boosting 40 : -0.3665079 
boosting mean 40 : -0.4873466 
boosting RMSE 40 : 0.1693821 

forest 40 : -0.3090048 
forest mean 40 : -0.3699883 
forest RMSE 40 : 0.06311625 

nnet 40 : -0.4474815 
nnet mean 40 : -0.4268178 
nnet RMSE 40 : 0.1355428 


s: 41 
logit 41 : -0.3957438 
logit mean 41 : -0.4311536 
logit RMSE 41 : 0.07082766 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 41 : -0.4047419 
boosting mean 41 : -0.4853318 
boosting RMSE 41 : 0.1673053 

forest 41 : -0.3302584 
forest mean 41 : -0.3690192 
forest RMSE 41 : 0.0632861 

nnet 41 : -0.4505754 
nnet mean 41 : -0.4273972 
nnet RMSE 41 : 0.1341124 


s: 42 
logit 42 : -0.4515333 
logit mean 42 : -0.4316388 
logit RMSE 42 : 0.07042972 

boosting 42 : -0.4930688 
boosting mean 42 : -0.485516 
boosting RMSE 42 : 0.1659242 

forest 42 : -0.3945767 
forest mean 42 : -0.3696277 
forest RMSE 42 : 0.06253375 

nnet 42 : -0.4957606 
nnet mean 42 : -0.4290249 
nnet RMSE 42 : 0.1333275 


s: 43 
logit 43 : -0.3989463 
logit mean 43 : -0.4308785 
logit RMSE 43 : 0.06960614 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 43 : -0.5346253 
boosting mean 43 : -0.4866581 
boosting RMSE 43 : 0.1652637 

forest 43 : -0.3594593 
forest mean 43 : -0.3693913 
forest RMSE 43 : 0.0621108 

nnet 43 : -0.2033504 
nnet mean 43 : -0.4237767 
nnet RMSE 43 : 0.1351375 


s: 44 
logit 44 : -0.4584575 
logit mean 44 : -0.4315053 
logit RMSE 44 : 0.06937266 

boosting 44 : -0.3267674 
boosting mean 44 : -0.4830242 
boosting RMSE 44 : 0.1637475 

forest 44 : -0.4088067 
forest mean 44 : -0.3702871 
forest RMSE 44 : 0.06141529 

nnet 44 : -0.2425704 
nnet mean 44 : -0.4196584 
nnet RMSE 44 : 0.1356848 


s: 45 
logit 45 : -0.3563885 
logit mean 45 : -0.4298360 
logit RMSE 45 : 0.0689049 

boosting 45 : -0.3348824 
boosting mean 45 : -0.4797322 
boosting RMSE 45 : 0.1622086 

forest 45 : -0.4478774 
forest mean 45 : -0.3720113 
forest RMSE 45 : 0.06114702 

nnet 45 : -0.2828415 
nnet mean 45 : -0.416618 
nnet RMSE 45 : 0.1353007 


s: 46 
logit 46 : -0.4529987 
logit mean 46 : -0.4303396 
logit RMSE 46 : 0.06859835 

boosting 46 : -0.4843139 
boosting mean 46 : -0.4798318 
boosting RMSE 46 : 0.1609166 

forest 46 : -0.3331715 
forest mean 46 : -0.371167 
forest RMSE 46 : 0.06127613 

nnet 46 : -0.5255894 
nnet mean 46 : -0.4189869 
nnet RMSE 46 : 0.1350970 


s: 47 
logit 47 : -0.4162622 
logit mean 47 : -0.4300401 
logit RMSE 47 : 0.0679061 

boosting 47 : -0.5168385 
boosting mean 47 : -0.4806192 
boosting RMSE 47 : 0.1601052 

forest 47 : -0.3198605 
forest mean 47 : -0.3700753 
forest RMSE 47 : 0.06173752 

nnet 47 : -0.4809961 
nnet mean 47 : -0.4203063 
nnet RMSE 47 : 0.1341733 


s: 48 
logit 48 : -0.4596847 
logit mean 48 : -0.4306577 
logit RMSE 48 : 0.067745 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 48 : -0.4958171 
boosting mean 48 : -0.4809358 
boosting RMSE 48 : 0.1590312 

forest 48 : -0.3930254 
forest mean 48 : -0.3705535 
forest RMSE 48 : 0.06109933 

nnet 48 : -0.4980005 
nnet mean 48 : -0.4219249 
nnet RMSE 48 : 0.1335197 


s: 49 
logit 49 : -0.5416636 
logit mean 49 : -0.4329231 
logit RMSE 49 : 0.07003775 

boosting 49 : -0.4454236 
boosting mean 49 : -0.480211 
boosting RMSE 49 : 0.1575337 

forest 49 : -0.4004215 
forest mean 49 : -0.371163 
forest RMSE 49 : 0.06047268 

nnet 49 : -0.3958291 
nnet mean 49 : -0.4213923 
nnet RMSE 49 : 0.1321515 


s: 50 
logit 50 : -0.4296382 
logit mean 50 : -0.4328574 
logit RMSE 50 : 0.06946041 

boosting 50 : -0.3975966 
boosting mean 50 : -0.4785588 
boosting RMSE 50 : 0.1559508 

forest 50 : -0.4172293 
forest mean 50 : -0.3720843 
forest RMSE 50 : 0.05991447 

nnet 50 : -0.4012552 
nnet mean 50 : -0.4209896 
nnet RMSE 50 : 0.1308235 


s: 51 
logit 51 : -0.3629242 
logit mean 51 : -0.4314861 
logit RMSE 51 : 0.06897173 

boosting 51 : -0.4970307 
boosting mean 51 : -0.4789209 
boosting RMSE 51 : 0.1550109 

forest 51 : -0.3747245 
forest mean 51 : -0.3721361 
forest RMSE 51 : 0.05942964 

nnet 51 : -0.4483411 
nnet mean 51 : -0.4215259 
nnet RMSE 51 : 0.1297113 


s: 52 
logit 52 : -0.3998548 
logit mean 52 : -0.4308779 
logit RMSE 52 : 0.06830532 

boosting 52 : -0.4430208 
boosting mean 52 : -0.4782306 
boosting RMSE 52 : 0.1536291 

forest 52 : -0.2999712 
forest mean 52 : -0.3707483 
forest RMSE 52 : 0.06046801 

nnet 52 : -0.8405019 
nnet mean 52 : -0.4295831 
nnet RMSE 52 : 0.1422429 


s: 53 
logit 53 : -0.4341232 
logit mean 53 : -0.4309391 
logit RMSE 53 : 0.06782003 

boosting 53 : -0.3638865 
boosting mean 53 : -0.4760731 
boosting RMSE 53 : 0.1522537 

forest 53 : -0.2998991 
forest mean 53 : -0.3694115 
forest RMSE 53 : 0.06145285 

nnet 53 : -0.2628439 
nnet mean 53 : -0.4264371 
nnet RMSE 53 : 0.1421486 


s: 54 
logit 54 : -0.6398322 
logit mean 54 : -0.4348075 
logit RMSE 54 : 0.07469642 

boosting 54 : -0.4339949 
boosting mean 54 : -0.4752939 
boosting RMSE 54 : 0.1509083 

forest 54 : -0.3559322 
forest mean 54 : -0.3691619 
forest RMSE 54 : 0.06117582 

nnet 54 : -0.5430399 
nnet mean 54 : -0.4285964 
nnet RMSE 54 : 0.1421651 


s: 55 
logit 55 : -0.3512745 
logit mean 55 : -0.4332887 
logit RMSE 55 : 0.07430528 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 55 : -0.3046282 
boosting mean 55 : -0.4721909 
boosting RMSE 55 : 0.1500821 

forest 55 : -0.3868134 
forest mean 55 : -0.3694829 
forest RMSE 55 : 0.06064319 

nnet 55 : -0.5616005 
nnet mean 55 : -0.4310147 
nnet RMSE 55 : 0.1425421 


s: 56 
logit 56 : -0.4463661 
logit mean 56 : -0.4335222 
logit RMSE 56 : 0.07389906 

boosting 56 : -0.6866502 
boosting mean 56 : -0.4760205 
boosting RMSE 56 : 0.1535894 

forest 56 : -0.3229101 
forest mean 56 : -0.3686512 
forest RMSE 56 : 0.0609758 

nnet 56 : -0.2425549 
nnet mean 56 : -0.4276493 
nnet RMSE 56 : 0.1428219 


s: 57 
logit 57 : -0.5033495 
logit mean 57 : -0.4347473 
logit RMSE 57 : 0.07451611 

boosting 57 : -0.5773967 
boosting mean 57 : -0.4777990 
boosting RMSE 57 : 0.1540387 

forest 57 : -0.3299833 
forest mean 57 : -0.3679728 
forest RMSE 57 : 0.06114593 

nnet 57 : -0.3608881 
nnet mean 57 : -0.4264781 
nnet RMSE 57 : 0.1416583 


s: 58 
logit 58 : -0.4446407 
logit mean 58 : -0.4349178 
logit RMSE 58 : 0.07410313 

boosting 58 : -0.4613728 
boosting mean 58 : -0.4775158 
boosting RMSE 58 : 0.1529175 

forest 58 : -0.4054999 
forest mean 58 : -0.3686198 
forest RMSE 58 : 0.06062082 

nnet 58 : -0.3264454 
nnet mean 58 : -0.4247534 
nnet RMSE 58 : 0.1407635 


s: 59 
logit 59 : -0.3493068 
logit mean 59 : -0.4334668 
logit RMSE 59 : 0.07376827 

boosting 59 : -0.5082712 
boosting mean 59 : -0.4780371 
boosting RMSE 59 : 0.1522699 

forest 59 : -0.4351369 
forest mean 59 : -0.3697472 
forest RMSE 59 : 0.06027871 

nnet 59 : -0.4939253 
nnet mean 59 : -0.4259258 
nnet RMSE 59 : 0.1401002 


s: 60 
logit 60 : -0.4378027 
logit mean 60 : -0.4335391 
logit RMSE 60 : 0.07331356 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 60 : -0.5488603 
boosting mean 60 : -0.4792175 
boosting RMSE 60 : 0.1522137 

forest 60 : -0.399602 
forest mean 60 : -0.3702448 
forest RMSE 60 : 0.0597743 

nnet 60 : -0.5185962 
nnet mean 60 : -0.4274703 
nnet RMSE 60 : 0.1397689 


s: 61 
logit 61 : -0.4862783 
logit mean 61 : -0.4344036 
logit RMSE 61 : 0.07354453 

boosting 61 : -0.6195113 
boosting mean 61 : -0.4815174 
boosting RMSE 61 : 0.1535549 

forest 61 : -0.4002372 
forest mean 61 : -0.3707365 
forest RMSE 61 : 0.05928233 

nnet 61 : -0.2705298 
nnet mean 61 : -0.4248975 
nnet RMSE 61 : 0.1396062 


s: 62 
logit 62 : -0.4711274 
logit mean 62 : -0.434996 
logit RMSE 62 : 0.07350617 

boosting 62 : -0.7601014 
boosting mean 62 : -0.4860107 
boosting RMSE 62 : 0.1590293 

forest 62 : -0.3157377 
forest mean 62 : -0.3698494 
forest RMSE 62 : 0.05976813 

nnet 62 : -0.3458441 
nnet mean 62 : -0.4236224 
nnet RMSE 62 : 0.1386464 


s: 63 
logit 63 : -0.4947975 
logit mean 63 : -0.4359452 
logit RMSE 63 : 0.07389206 

boosting 63 : -0.5893765 
boosting mean 63 : -0.4876514 
boosting RMSE 63 : 0.1595561 

forest 63 : -0.4164052 
forest mean 63 : -0.3705884 
forest RMSE 63 : 0.05932789 

nnet 63 : -0.7502514 
nnet mean 63 : -0.428807 
nnet RMSE 63 : 0.1444471 


s: 64 
logit 64 : -0.5280137 
logit mean 64 : -0.4373838 
logit RMSE 64 : 0.07503852 

boosting 64 : -0.4575322 
boosting mean 64 : -0.4871808 
boosting RMSE 64 : 0.1584679 

forest 64 : -0.4090298 
forest mean 64 : -0.3711891 
forest RMSE 64 : 0.05887339 

nnet 64 : -0.6968634 
nnet mean 64 : -0.4329954 
nnet RMSE 64 : 0.1480403 


s: 65 
logit 65 : -0.4478431 
logit mean 65 : -0.4375447 
logit RMSE 65 : 0.07469516 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 65 : -0.4701861 
boosting mean 65 : -0.4869193 
boosting RMSE 65 : 0.1574850 

forest 65 : -0.410879 
forest mean 65 : -0.3717997 
forest RMSE 65 : 0.05843435 

nnet 65 : -0.3672899 
nnet mean 65 : -0.4319845 
nnet RMSE 65 : 0.1469531 


s: 66 
logit 66 : -0.5060759 
logit mean 66 : -0.438583 
logit RMSE 66 : 0.0752683 

boosting 66 : -0.5546682 
boosting mean 66 : -0.4879458 
boosting RMSE 66 : 0.1574427 

forest 66 : -0.4217115 
forest mean 66 : -0.3725559 
forest RMSE 66 : 0.05805152 

nnet 66 : -0.3585889 
nnet mean 66 : -0.4308725 
nnet RMSE 66 : 0.1459247 


s: 67 
logit 67 : -0.480303 
logit mean 67 : -0.4392057 
logit RMSE 67 : 0.07534592 

boosting 67 : -0.5957161 
boosting mean 67 : -0.4895544 
boosting RMSE 67 : 0.1580821 

forest 67 : -0.3803299 
forest mean 67 : -0.3726719 
forest RMSE 67 : 0.05766676 

nnet 67 : -0.7027484 
nnet mean 67 : -0.4349303 
nnet RMSE 67 : 0.1494798 


s: 68 
logit 68 : -0.5168221 
logit mean 68 : -0.4403471 
logit RMSE 68 : 0.07611977 

boosting 68 : -0.7026241 
boosting mean 68 : -0.4926877 
boosting RMSE 68 : 0.1611497 

forest 68 : -0.3066081 
forest mean 68 : -0.3717004 
forest RMSE 68 : 0.05835081 

nnet 68 : -0.4538744 
nnet mean 68 : -0.4352089 
nnet RMSE 68 : 0.1485203 


s: 69 
logit 69 : -0.4128022 
logit mean 69 : -0.4399479 
logit RMSE 69 : 0.07558188 

boosting 69 : -0.428181 
boosting mean 69 : -0.4917529 
boosting RMSE 69 : 0.1600136 

forest 69 : -0.3982575 
forest mean 69 : -0.3720853 
forest RMSE 69 : 0.05792682 

nnet 69 : -0.4586230 
nnet mean 69 : -0.4355483 
nnet RMSE 69 : 0.1476090 


s: 70 
logit 70 : -0.2596994 
logit mean 70 : -0.4373730 
logit RMSE 70 : 0.07689093 

boosting 70 : -0.4465268 
boosting mean 70 : -0.4911068 
boosting RMSE 70 : 0.1589639 

forest 70 : -0.2918148 
forest mean 70 : -0.3709386 
forest RMSE 70 : 0.05894727 

nnet 70 : -0.4167051 
nnet mean 70 : -0.4352791 
nnet RMSE 70 : 0.1465644 


s: 71 
logit 71 : -0.3529121 
logit mean 71 : -0.4361834 
logit RMSE 71 : 0.07655177 

boosting 71 : -0.4396794 
boosting mean 71 : -0.4903824 
boosting RMSE 71 : 0.1579107 

forest 71 : -0.3569047 
forest mean 71 : -0.3707409 
forest RMSE 71 : 0.05875371 

nnet 71 : -0.6092218 
nnet mean 71 : -0.437729 
nnet RMSE 71 : 0.1476317 


s: 72 
logit 72 : -0.3263165 
logit mean 72 : -0.4346574 
logit RMSE 72 : 0.07651267 

boosting 72 : -0.4211572 
boosting mean 72 : -0.489421 
boosting RMSE 72 : 0.1568301 

forest 72 : -0.3385963 
forest mean 72 : -0.3702945 
forest RMSE 72 : 0.05879133 

nnet 72 : -0.2580613 
nnet mean 72 : -0.4352336 
nnet RMSE 72 : 0.1475541 


s: 73 
logit 73 : -0.4481896 
logit mean 73 : -0.4348428 
logit RMSE 73 : 0.07619584 

boosting 73 : -0.4974483 
boosting mean 73 : -0.4895309 
boosting RMSE 73 : 0.1561692 

forest 73 : -0.4270857 
forest mean 73 : -0.3710724 
forest RMSE 73 : 0.05847326 

nnet 73 : -0.3958872 
nnet mean 73 : -0.4346946 
nnet RMSE 73 : 0.1465408 


s: 74 
logit 74 : -0.4401398 
logit mean 74 : -0.4349144 
logit RMSE 74 : 0.07582296 

boosting 74 : -0.4961828 
boosting mean 74 : -0.4896208 
boosting RMSE 74 : 0.1555129 

forest 74 : -0.3545566 
forest mean 74 : -0.3708492 
forest RMSE 74 : 0.05831659 

nnet 74 : -0.8214267 
nnet mean 74 : -0.4399207 
nnet RMSE 74 : 0.1535709 


s: 75 
logit 75 : -0.4174594 
logit mean 75 : -0.4346817 
logit RMSE 75 : 0.07534276 

boosting 75 : -0.2875555 
boosting mean 75 : -0.4869266 
boosting RMSE 75 : 0.1550174 

forest 75 : -0.2634990 
forest mean 75 : -0.3694179 
forest RMSE 75 : 0.0600326 

nnet 75 : -0.0882307 
nnet mean 75 : -0.4352315 
nnet RMSE 75 : 0.1567341 


s: 76 
logit 76 : -0.3814782 
logit mean 76 : -0.4339816 
logit RMSE 76 : 0.07487559 

boosting 76 : -0.4122564 
boosting mean 76 : -0.4859441 
boosting RMSE 76 : 0.1540006 

forest 76 : -0.3862919 
forest mean 76 : -0.3696399 
forest RMSE 76 : 0.05965707 

nnet 76 : -0.6373176 
nnet mean 76 : -0.4378905 
nnet RMSE 76 : 0.1580613 


s: 77 
logit 77 : -0.3828305 
logit mean 77 : -0.4333173 
logit RMSE 77 : 0.07441352 

boosting 77 : -0.4362278 
boosting mean 77 : -0.4852985 
boosting RMSE 77 : 0.153053 

forest 77 : -0.3998893 
forest mean 77 : -0.3700328 
forest RMSE 77 : 0.05926842 

nnet 77 : -0.3788308 
nnet mean 77 : -0.4371235 
nnet RMSE 77 : 0.1570501 


s: 78 
logit 78 : -0.3750165 
logit mean 78 : -0.4325699 
logit RMSE 78 : 0.07398907 

boosting 78 : -0.3595609 
boosting mean 78 : -0.4836864 
boosting RMSE 78 : 0.1521376 

forest 78 : -0.4190032 
forest mean 78 : -0.3706606 
forest RMSE 78 : 0.05892657 

nnet 78 : -0.3220290 
nnet mean 78 : -0.4356480 
nnet RMSE 78 : 0.1562897 


s: 79 
logit 79 : -0.3554838 
logit mean 79 : -0.4315941 
logit RMSE 79 : 0.0736897 

boosting 79 : -0.3457104 
boosting mean 79 : -0.4819399 
boosting RMSE 79 : 0.1512950 

forest 79 : -0.3881718 
forest mean 79 : -0.3708823 
forest RMSE 79 : 0.05856755 

nnet 79 : -0.2941925 
nnet mean 79 : -0.4338574 
nnet RMSE 79 : 0.1557530 


s: 80 
logit 80 : -0.5359223 
logit mean 80 : -0.4328982 
logit RMSE 80 : 0.0747879 

boosting 80 : -0.6210197 
boosting mean 80 : -0.4836784 
boosting RMSE 80 : 0.1523636 

forest 80 : -0.3547312 
forest mean 80 : -0.3706804 
forest RMSE 80 : 0.05842 

nnet 80 : -0.3550625 
nnet mean 80 : -0.4328724 
nnet RMSE 80 : 0.1548580 


s: 81 
logit 81 : -0.4496765 
logit mean 81 : -0.4331053 
logit RMSE 81 : 0.07452948 

boosting 81 : -0.4470276 
boosting mean 81 : -0.4832259 
boosting RMSE 81 : 0.1515103 

forest 81 : -0.3594241 
forest mean 81 : -0.3705414 
forest RMSE 81 : 0.05823305 

nnet 81 : -0.2431579 
nnet mean 81 : -0.4305303 
nnet RMSE 81 : 0.1548826 


s: 82 
logit 82 : -0.4096081 
logit mean 82 : -0.4328188 
logit RMSE 82 : 0.07408124 

boosting 82 : -0.5914916 
boosting mean 82 : -0.4845462 
boosting RMSE 82 : 0.1520612 

forest 82 : -0.4767508 
forest mean 82 : -0.3718366 
forest RMSE 82 : 0.0584942 

nnet 82 : -0.6105903 
nnet mean 82 : -0.4327261 
nnet RMSE 82 : 0.1556821 


s: 83 
logit 83 : -0.5369124 
logit mean 83 : -0.4340729 
logit RMSE 83 : 0.07515153 

boosting 83 : -0.4392548 
boosting mean 83 : -0.4840006 
boosting RMSE 83 : 0.1512038 

forest 83 : -0.4217097 
forest mean 83 : -0.3724375 
forest RMSE 83 : 0.05818957 

nnet 83 : -0.4512582 
nnet mean 83 : -0.4329494 
nnet RMSE 83 : 0.1548437 


s: 84 
logit 84 : -0.2829494 
logit mean 84 : -0.4322738 
logit RMSE 84 : 0.0757867 

boosting 84 : -0.4454762 
boosting mean 84 : -0.4835419 
boosting RMSE 84 : 0.150383 

forest 84 : -0.4003465 
forest mean 84 : -0.3727698 
forest RMSE 84 : 0.05784218 

nnet 84 : -0.2787674 
nnet mean 84 : -0.4311139 
nnet RMSE 84 : 0.1544865 


s: 85 
logit 85 : -0.3982462 
logit mean 85 : -0.4318735 
logit RMSE 85 : 0.07533981 

boosting 85 : -0.5624784 
boosting mean 85 : -0.4844706 
boosting RMSE 85 : 0.1505309 

forest 85 : -0.3559803 
forest mean 85 : -0.3725723 
forest RMSE 85 : 0.05769881 

nnet 85 : -0.7586729 
nnet mean 85 : -0.4349676 
nnet RMSE 85 : 0.158426 


s: 86 
logit 86 : -0.4748496 
logit mean 86 : -0.4323732 
logit RMSE 86 : 0.07533413 

boosting 86 : -0.4768124 
boosting mean 86 : -0.4843815 
boosting RMSE 86 : 0.1498822 

forest 86 : -0.3126748 
forest mean 86 : -0.3718758 
forest RMSE 86 : 0.05813014 

nnet 86 : -0.4449792 
nnet mean 86 : -0.435084 
nnet RMSE 86 : 0.1575769 


s: 87 
logit 87 : -0.3119409 
logit mean 87 : -0.4309889 
logit RMSE 87 : 0.07549258 

boosting 87 : -0.3833693 
boosting mean 87 : -0.4832205 
boosting RMSE 87 : 0.1490290 

forest 87 : -0.3860441 
forest mean 87 : -0.3720386 
forest RMSE 87 : 0.05781445 

nnet 87 : -0.402826 
nnet mean 87 : -0.4347132 
nnet RMSE 87 : 0.1566690 


s: 88 
logit 88 : -0.3572485 
logit mean 88 : -0.430151 
logit RMSE 88 : 0.07520064 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 88 : -0.5291589 
boosting mean 88 : -0.4837425 
boosting RMSE 88 : 0.1488181 

forest 88 : -0.4139453 
forest mean 88 : -0.3725148 
forest RMSE 88 : 0.05750424 

nnet 88 : -0.5038968 
nnet mean 88 : -0.4354994 
nnet RMSE 88 : 0.1561695 


s: 89 
logit 89 : -0.449812 
logit mean 89 : -0.4303719 
logit RMSE 89 : 0.07496315 

boosting 89 : -0.5984511 
boosting mean 89 : -0.4850314 
boosting RMSE 89 : 0.1494674 

forest 89 : -0.3806693 
forest mean 89 : -0.3726065 
forest RMSE 89 : 0.05721697 

nnet 89 : -0.4960277 
nnet mean 89 : -0.4361795 
nnet RMSE 89 : 0.1556229 


s: 90 
logit 90 : -0.2822097 
logit mean 90 : -0.4287257 
logit RMSE 90 : 0.07557246 

boosting 90 : -0.5364867 
boosting mean 90 : -0.4856031 
boosting RMSE 90 : 0.1493294 

forest 90 : -0.3646348 
forest mean 90 : -0.3725179 
forest RMSE 90 : 0.0570202 

nnet 90 : -0.496917 
nnet mean 90 : -0.4368543 
nnet RMSE 90 : 0.1550927 


s: 91 
logit 91 : -0.5291454 
logit mean 91 : -0.4298292 
logit RMSE 91 : 0.07636568 

boosting 91 : -0.437046 
boosting mean 91 : -0.4850695 
boosting RMSE 91 : 0.1485574 

forest 91 : -0.4244542 
forest mean 91 : -0.3730886 
forest RMSE 91 : 0.05676395 

nnet 91 : -0.3969522 
nnet mean 91 : -0.4364158 
nnet RMSE 91 : 0.1542385 


s: 92 
logit 92 : -0.4673345 
logit mean 92 : -0.4302368 
logit RMSE 92 : 0.07627327 

boosting 92 : -0.7834077 
boosting mean 92 : -0.4883123 
boosting RMSE 92 : 0.1530596 

forest 92 : -0.4324133 
forest mean 92 : -0.3737335 
forest RMSE 92 : 0.05655566 

nnet 92 : -0.6611117 
nnet mean 92 : -0.4388582 
nnet RMSE 92 : 0.1557948 


s: 93 
logit 93 : -0.604058 
logit mean 93 : -0.4321059 
logit RMSE 93 : 0.07875782 

boosting 93 : -0.6791794 
boosting mean 93 : -0.4903646 
boosting RMSE 93 : 0.1549626 

forest 93 : -0.3182641 
forest mean 93 : -0.373137 
forest RMSE 93 : 0.05688573 

nnet 93 : -0.3915498 
nnet mean 93 : -0.4383495 
nnet RMSE 93 : 0.1549574 


s: 94 
logit 94 : -0.4820082 
logit mean 94 : -0.4326368 
logit RMSE 94 : 0.0787931 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 94 : -0.5334507 
boosting mean 94 : -0.490823 
boosting RMSE 94 : 0.1547495 

forest 94 : -0.4664537 
forest mean 94 : -0.3741297 
forest RMSE 94 : 0.05699597 

nnet 94 : -0.3654369 
nnet mean 94 : -0.4375738 
nnet RMSE 94 : 0.1541722 


s: 95 
logit 95 : -0.4181384 
logit mean 95 : -0.4324841 
logit RMSE 95 : 0.0783994 

boosting 95 : -0.5742944 
boosting mean 95 : -0.4917017 
boosting RMSE 95 : 0.1549681 

forest 95 : -0.4938323 
forest mean 95 : -0.3753898 
forest RMSE 95 : 0.05750673 

nnet 95 : -0.3320379 
nnet mean 95 : -0.4364629 
nnet RMSE 95 : 0.1535171 


s: 96 
logit 96 : -0.4360234 
logit mean 96 : -0.432521 
logit RMSE 96 : 0.07807661 

boosting 96 : -0.4336139 
boosting mean 96 : -0.4910966 
boosting RMSE 96 : 0.1541970 

forest 96 : -0.3371911 
forest mean 96 : -0.3749919 
forest RMSE 96 : 0.05756448 

nnet 96 : -0.6308333 
nnet mean 96 : -0.4384876 
nnet RMSE 96 : 0.1545220 


s: 97 
logit 97 : -0.4742294 
logit mean 97 : -0.432951 
logit RMSE 97 : 0.07803792 

boosting 97 : -0.5034494 
boosting mean 97 : -0.4912239 
boosting RMSE 97 : 0.1537593 

forest 97 : -0.4033433 
forest mean 97 : -0.3752841 
forest RMSE 97 : 0.05726799 

nnet 97 : -0.7186301 
nnet mean 97 : -0.4413757 
nnet RMSE 97 : 0.1570908 


s: 98 
logit 98 : -0.4525266 
logit mean 98 : -0.4331507 
logit RMSE 98 : 0.07781985 

boosting 98 : -0.6236372 
boosting mean 98 : -0.4925751 
boosting RMSE 98 : 0.1546319 

forest 98 : -0.4084194 
forest mean 98 : -0.3756223 
forest RMSE 98 : 0.05698141 

nnet 98 : -0.3332992 
nnet mean 98 : -0.4402729 
nnet RMSE 98 : 0.1564325 


s: 99 
logit 99 : -0.4189992 
logit mean 99 : -0.4330078 
logit RMSE 99 : 0.07744936 

boosting 99 : -0.3665931 
boosting mean 99 : -0.4913025 
boosting RMSE 99 : 0.1538856 

forest 99 : -0.4136275 
forest mean 99 : -0.3760062 
forest RMSE 99 : 0.05670943 

nnet 99 : -0.5109071 
nnet mean 99 : -0.4409863 
nnet RMSE 99 : 0.1560390 


s: 100 
logit 100 : -0.3874506 
logit mean 100 : -0.4325522 
logit RMSE 100 : 0.07707136 

boosting 100 : -0.4718721 
boosting mean 100 : -0.4911082 
boosting RMSE 100 : 0.1532828 

forest 100 : -0.3289948 
forest mean 100 : -0.375536 
forest RMSE 100 : 0.05687018 

nnet 100 : -0.2700797 
nnet mean 100 : -0.4392773 
nnet RMSE 100 : 0.1557995 


s: 101 
logit 101 : -0.4284508 
logit mean 101 : -0.4325116 
logit RMSE 101 : 0.0767411 

boosting 101 : -0.704397 
boosting mean 101 : -0.49322 
boosting RMSE 101 : 0.1555005 

forest 101 : -0.3033807 
forest mean 101 : -0.3748216 
forest RMSE 101 : 0.05739882 

nnet 101 : -0.6205589 
nnet mean 101 : -0.4410721 
nnet RMSE 101 : 0.1565720 


s: 102 
logit 102 : -0.4441923 
logit mean 102 : -0.4326261 
logit RMSE 102 : 0.07648926 

boosting 102 : -0.5885789 
boosting mean 102 : -0.4941549 
boosting RMSE 102 : 0.1558589 

forest 102 : -0.3869905 
forest mean 102 : -0.3749409 
forest RMSE 102 : 0.05713128 

nnet 102 : -0.4092787 
nnet mean 102 : -0.4407604 
nnet RMSE 102 : 0.1558054 


s: 103 
logit 103 : -0.4894880 
logit mean 103 : -0.4331782 
logit RMSE 103 : 0.07662606 

boosting 103 : -0.5958102 
boosting mean 103 : -0.4951418 
boosting RMSE 103 : 0.1562958 

forest 103 : -0.3943385 
forest mean 103 : -0.3751293 
forest RMSE 103 : 0.056856 

nnet 103 : -0.5442728 
nnet mean 103 : -0.4417654 
nnet RMSE 103 : 0.1556975 


s: 104 
logit 104 : -0.3683096 
logit mean 104 : -0.4325545 
logit RMSE 104 : 0.07632007 

boosting 104 : -0.1734388 
boosting mean 104 : -0.4920485 
boosting RMSE 104 : 0.1571212 

forest 104 : -0.4743009 
forest mean 104 : -0.3760828 
forest RMSE 104 : 0.05704915 

nnet 104 : -0.5578502 
nnet mean 104 : -0.4428816 
nnet RMSE 104 : 0.1557183 


s: 105 
logit 105 : -0.3936197 
logit mean 105 : -0.4321836 
logit RMSE 105 : 0.07595832 

boosting 105 : -0.5048125 
boosting mean 105 : -0.4921701 
boosting RMSE 105 : 0.1567054 

forest 105 : -0.4140701 
forest mean 105 : -0.3764446 
forest RMSE 105 : 0.05679344 

nnet 105 : -0.4239524 
nnet mean 105 : -0.4427013 
nnet RMSE 105 : 0.1549927 


s: 106 
logit 106 : -0.4888831 
logit mean 106 : -0.4327185 
logit RMSE 106 : 0.07609051 

boosting 106 : -0.679016 
boosting mean 106 : -0.4939328 
boosting RMSE 106 : 0.1583014 

forest 106 : -0.4671644 
forest mean 106 : -0.3773005 
forest RMSE 106 : 0.05690011 

nnet 106 : -0.566763 
nnet mean 106 : -0.4438717 
nnet RMSE 106 : 0.1551079 


s: 107 
logit 107 : -0.4135565 
logit mean 107 : -0.4325395 
logit RMSE 107 : 0.07574545 

boosting 107 : -0.620776 
boosting mean 107 : -0.4951182 
boosting RMSE 107 : 0.1589990 

forest 107 : -0.3629393 
forest mean 107 : -0.3771662 
forest RMSE 107 : 0.05674681 

nnet 107 : -0.4172833 
nnet mean 107 : -0.4436232 
nnet RMSE 107 : 0.1543904 


s: 108 
logit 108 : -0.3977529 
logit mean 108 : -0.4322174 
logit RMSE 108 : 0.07539427 

boosting 108 : -0.4588037 
boosting mean 108 : -0.494782 
boosting RMSE 108 : 0.1583623 

forest 108 : -0.4530808 
forest mean 108 : -0.3778692 
forest RMSE 108 : 0.05671396 

nnet 108 : -0.4925631 
nnet mean 108 : -0.4440764 
nnet RMSE 108 : 0.1539319 


s: 109 
logit 109 : -0.43815 
logit mean 109 : -0.4322718 
logit RMSE 109 : 0.07513654 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 109 : -0.4176411 
boosting mean 109 : -0.4940743 
boosting RMSE 109 : 0.1576432 

forest 109 : -0.3421475 
forest mean 109 : -0.3775414 
forest RMSE 109 : 0.0567245 

nnet 109 : -0.3849505 
nnet mean 109 : -0.4435339 
nnet RMSE 109 : 0.1532309 


s: 110 
logit 110 : -0.3980545 
logit mean 110 : -0.4319607 
logit RMSE 110 : 0.07479446 

boosting 110 : -0.5927055 
boosting mean 110 : -0.4949709 
boosting RMSE 110 : 0.157997 

forest 110 : -0.4027396 
forest mean 110 : -0.3777705 
forest RMSE 110 : 0.05646668 

nnet 110 : -0.3144250 
nnet mean 110 : -0.4423602 
nnet RMSE 110 : 0.1527509 


s: 111 
logit 111 : -0.3673994 
logit mean 111 : -0.4313791 
logit RMSE 111 : 0.07452105 

boosting 111 : -0.5411583 
boosting mean 111 : -0.495387 
boosting RMSE 111 : 0.1578533 

forest 111 : -0.3772619 
forest mean 111 : -0.3777659 
forest RMSE 111 : 0.05625317 

nnet 111 : -0.2034915 
nnet mean 111 : -0.4402083 
nnet RMSE 111 : 0.1532009 


s: 112 
logit 112 : -0.5295773 
logit mean 112 : -0.4322559 
logit RMSE 112 : 0.0751912 

boosting 112 : -0.7685415 
boosting mean 112 : -0.4978259 
boosting RMSE 112 : 0.1609593 

forest 112 : -0.3844941 
forest mean 112 : -0.377826 
forest RMSE 112 : 0.05602064 

nnet 112 : -0.2162066 
nnet mean 112 : -0.4382082 
nnet RMSE 112 : 0.1535011 


s: 113 
logit 113 : -0.3873349 
logit mean 113 : -0.4318583 
logit RMSE 113 : 0.07486724 

boosting 113 : -0.4734292 
boosting mean 113 : -0.49761 
boosting RMSE 113 : 0.1603943 

forest 113 : -0.2979688 
forest mean 113 : -0.3771193 
forest RMSE 113 : 0.0565921 

nnet 113 : -0.3655105 
nnet mean 113 : -0.4375649 
nnet RMSE 113 : 0.1528548 


s: 114 
logit 114 : -0.4600083 
logit mean 114 : -0.4321053 
logit RMSE 114 : 0.07474974 

boosting 114 : -0.3535788 
boosting mean 114 : -0.4963466 
boosting RMSE 114 : 0.1597485 

forest 114 : -0.3688565 
forest mean 114 : -0.3770468 
forest RMSE 114 : 0.0564188 

nnet 114 : -0.3179806 
nnet mean 114 : -0.4365159 
nnet RMSE 114 : 0.1523766 


s: 115 
logit 115 : -0.5093236 
logit mean 115 : -0.4327767 
logit RMSE 115 : 0.075119 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 115 : -0.5192388 
boosting mean 115 : -0.4965456 
boosting RMSE 115 : 0.1594406 

forest 115 : -0.3520305 
forest mean 115 : -0.3768293 
forest RMSE 115 : 0.05635079 

nnet 115 : -0.1991661 
nnet mean 115 : -0.434452 
nnet RMSE 115 : 0.1528642 


s: 116 
logit 116 : -0.4527116 
logit mean 116 : -0.4329486 
logit RMSE 116 : 0.07495446 

boosting 116 : -0.3971937 
boosting mean 116 : -0.4956892 
boosting RMSE 116 : 0.1587521 

forest 116 : -0.3364922 
forest mean 116 : -0.3764816 
forest RMSE 116 : 0.05641637 

nnet 116 : -0.5281598 
nnet mean 116 : -0.4352598 
nnet RMSE 116 : 0.1526683 


s: 117 
logit 117 : -0.4103712 
logit mean 117 : -0.4327556 
logit RMSE 117 : 0.07463961 

boosting 117 : -0.528901 
boosting mean 117 : -0.495973 
boosting RMSE 117 : 0.1585207 

forest 117 : -0.3441837 
forest mean 117 : -0.3762055 
forest RMSE 117 : 0.05641126 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Warning in MatchLoopCfast(N = s1$N, xvars = Kx, All = s1$All, M = s1$M,  :
  Increasing memory because of ties.  I would be faster with the ties=FALSE option.

nnet 117 : -0.4539895 
nnet mean 117 : -0.4354199 
nnet RMSE 117 : 0.1520964 


s: 118 
logit 118 : -0.4710434 
logit mean 118 : -0.4330801 
logit RMSE 118 : 0.07460986 

boosting 118 : -0.4281811 
boosting mean 118 : -0.4953985 
boosting RMSE 118 : 0.1578689 

forest 118 : -0.3981465 
forest mean 118 : -0.3763914 
forest RMSE 118 : 0.05617198 

nnet 118 : -0.1818488 
nnet mean 118 : -0.433271 
nnet RMSE 118 : 0.1527763 


s: 119 
logit 119 : -0.4369481 
logit mean 119 : -0.4331126 
logit RMSE 119 : 0.07437288 

boosting 119 : -0.5308456 
boosting mean 119 : -0.4956964 
boosting RMSE 119 : 0.1576611 

forest 119 : -0.4465988 
forest mean 119 : -0.3769814 
forest RMSE 119 : 0.05609834 

nnet 119 : -0.2489786 
nnet mean 119 : -0.4317223 
nnet RMSE 119 : 0.1527616 


s: 120 
logit 120 : -0.4308532 
logit mean 120 : -0.4330938 
logit RMSE 120 : 0.07411588 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 120 : -0.4655566 
boosting mean 120 : -0.4954452 
boosting RMSE 120 : 0.1571169 

forest 120 : -0.466033 
forest mean 120 : -0.3777235 
forest RMSE 120 : 0.05618839 

nnet 120 : -0.7473377 
nnet mean 120 : -0.4343525 
nnet RMSE 120 : 0.1553930 


s: 121 
logit 121 : -0.3741021 
logit mean 121 : -0.4326062 
logit RMSE 121 : 0.07384652 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 121 : -0.504801 
boosting mean 121 : -0.4955226 
boosting RMSE 121 : 0.1567561 

forest 121 : -0.4386434 
forest mean 121 : -0.378227 
forest RMSE 121 : 0.0560659 

nnet 121 : -0.5242085 
nnet mean 121 : -0.4350951 
nnet RMSE 121 : 0.155161 


s: 122 
logit 122 : -0.4467996 
logit mean 122 : -0.4327226 
logit RMSE 122 : 0.0736652 

boosting 122 : -0.5452443 
boosting mean 122 : -0.4959301 
boosting RMSE 122 : 0.1566651 

forest 122 : -0.3952463 
forest mean 122 : -0.3783665 
forest RMSE 122 : 0.0558373 

nnet 122 : -0.2589796 
nnet mean 122 : -0.4336515 
nnet RMSE 122 : 0.1550503 


s: 123 
logit 123 : -0.4210762 
logit mean 123 : -0.4326279 
logit RMSE 123 : 0.07338975 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 123 : -0.5036561 
boosting mean 123 : -0.4959929 
boosting RMSE 123 : 0.1563067 

forest 123 : -0.4531743 
forest mean 123 : -0.3789747 
forest RMSE 123 : 0.05581617 

nnet 123 : -0.4467858 
nnet mean 123 : -0.4337583 
nnet RMSE 123 : 0.1544764 


s: 124 
logit 124 : -0.3740662 
logit mean 124 : -0.4321556 
logit RMSE 124 : 0.07313031 

boosting 124 : -0.5441828 
boosting mean 124 : -0.4963815 
boosting RMSE 124 : 0.1562127 

forest 124 : -0.4658751 
forest mean 124 : -0.3796755 
forest RMSE 124 : 0.05590453 

nnet 124 : -0.3916804 
nnet mean 124 : -0.4334189 
nnet RMSE 124 : 0.1538540 


s: 125 
logit 125 : -0.3500876 
logit mean 125 : -0.4314991 
logit RMSE 125 : 0.07297389 

boosting 125 : -0.5775283 
boosting mean 125 : -0.4970307 
boosting RMSE 125 : 0.1563947 

forest 125 : -0.3586920 
forest mean 125 : -0.3795076 
forest RMSE 125 : 0.05580291 

nnet 125 : -0.1317635 
nnet mean 125 : -0.4310057 
nnet RMSE 125 : 0.1551042 


s: 126 
logit 126 : -0.3746265 
logit mean 126 : -0.4310477 
logit RMSE 126 : 0.07271887 

boosting 126 : -0.4941647 
boosting mean 126 : -0.497008 
boosting RMSE 126 : 0.1559986 

forest 126 : -0.4099410 
forest mean 126 : -0.3797492 
forest RMSE 126 : 0.05558808 

nnet 126 : -0.4121743 
nnet mean 126 : -0.4308562 
nnet RMSE 126 : 0.1544913 


s: 127 
logit 127 : -0.3651136 
logit mean 127 : -0.4305285 
logit RMSE 127 : 0.07249814 

boosting 127 : -0.4554473 
boosting mean 127 : -0.4966807 
boosting RMSE 127 : 0.1554611 

forest 127 : -0.3366886 
forest mean 127 : -0.3794101 
forest RMSE 127 : 0.05565308 

nnet 127 : -0.2294622 
nnet mean 127 : -0.4292705 
nnet RMSE 127 : 0.1546241 


s: 128 
logit 128 : -0.3723422 
logit mean 128 : -0.4300739 
logit RMSE 128 : 0.07225575 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 128 : -0.5037052 
boosting mean 128 : -0.4967356 
boosting RMSE 128 : 0.1551237 

forest 128 : -0.3751068 
forest mean 128 : -0.3793765 
forest RMSE 128 : 0.05547891 

nnet 128 : -0.5489559 
nnet mean 128 : -0.4302055 
nnet RMSE 128 : 0.1545806 


s: 129 
logit 129 : -0.3787569 
logit mean 129 : -0.4296761 
logit RMSE 129 : 0.07199944 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 129 : -0.5684782 
boosting mean 129 : -0.4972917 
boosting RMSE 129 : 0.1552316 

forest 129 : -0.4946359 
forest mean 129 : -0.38027 
forest RMSE 129 : 0.05588806 

nnet 129 : -0.4248592 
nnet mean 129 : -0.4301641 
nnet RMSE 129 : 0.1539959 


s: 130 
logit 130 : -0.4751238 
logit mean 130 : -0.4300257 
logit RMSE 130 : 0.072024 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 130 : -0.5143114 
boosting mean 130 : -0.4974227 
boosting RMSE 130 : 0.1549581 

forest 130 : -0.369244 
forest mean 130 : -0.3801851 
forest RMSE 130 : 0.055738 

nnet 130 : -0.3924184 
nnet mean 130 : -0.4298737 
nnet RMSE 130 : 0.1534039 


s: 131 
logit 131 : -0.5327612 
logit mean 131 : -0.43081 
logit RMSE 131 : 0.07268014 

boosting 131 : -0.5264176 
boosting mean 131 : -0.497644 
boosting RMSE 131 : 0.1547602 

forest 131 : -0.4499298 
forest mean 131 : -0.3807175 
forest RMSE 131 : 0.05569596 

nnet 131 : -0.497632 
nnet mean 131 : -0.4303909 
nnet RMSE 131 : 0.1530551 


s: 132 
logit 132 : -0.3276142 
logit mean 132 : -0.4300282 
logit RMSE 132 : 0.07267792 

boosting 132 : -0.5700426 
boosting mean 132 : -0.4981925 
boosting RMSE 132 : 0.1548816 

forest 132 : -0.3832514 
forest mean 132 : -0.3807367 
forest RMSE 132 : 0.05550374 

nnet 132 : -0.5132667 
nnet mean 132 : -0.4310188 
nnet RMSE 132 : 0.1527927 


s: 133 
logit 133 : -0.3009776 
logit mean 133 : -0.4290579 
logit RMSE 133 : 0.07291152 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 133 : -0.4048232 
boosting mean 133 : -0.4974905 
boosting RMSE 133 : 0.1542988 

forest 133 : -0.3355102 
forest mean 133 : -0.3803967 
forest RMSE 133 : 0.05557672 

nnet 133 : -0.447187 
nnet mean 133 : -0.4311404 
nnet RMSE 133 : 0.1522722 


s: 134 
logit 134 : -0.3834756 
logit mean 134 : -0.4287177 
logit RMSE 134 : 0.07265298 

boosting 134 : -0.4353994 
boosting mean 134 : -0.4970271 
boosting RMSE 134 : 0.1537524 

forest 134 : -0.4202813 
forest mean 134 : -0.3806943 
forest RMSE 134 : 0.05539667 

nnet 134 : -0.4404331 
nnet mean 134 : -0.4312097 
nnet RMSE 134 : 0.1517431 


s: 135 
logit 135 : -0.3718155 
logit mean 135 : -0.4282962 
logit RMSE 135 : 0.07242403 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 135 : -0.4966718 
boosting mean 135 : -0.4970245 
boosting RMSE 135 : 0.1534077 

forest 135 : -0.3833809 
forest mean 135 : -0.3807142 
forest RMSE 135 : 0.05520965 

nnet 135 : -0.465618 
nnet mean 135 : -0.4314646 
nnet RMSE 135 : 0.1512855 


s: 136 
logit 136 : -0.4425552 
logit mean 136 : -0.4284011 
logit RMSE 136 : 0.07224948 

boosting 136 : -0.5080106 
boosting mean 136 : -0.4971052 
boosting RMSE 136 : 0.1531230 

forest 136 : -0.4129308 
forest mean 136 : -0.3809511 
forest RMSE 136 : 0.05501747 

nnet 136 : -0.675085 
nnet mean 136 : -0.4332559 
nnet RMSE 136 : 0.1525629 


s: 137 
logit 137 : -0.4083206 
logit mean 137 : -0.4282545 
logit RMSE 137 : 0.07198882 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 137 : -0.4143306 
boosting mean 137 : -0.496501 
boosting RMSE 137 : 0.1525681 

forest 137 : -0.2993929 
forest mean 137 : -0.3803558 
forest RMSE 137 : 0.05548612 

nnet 137 : -0.4535796 
nnet mean 137 : -0.4334043 
nnet RMSE 137 : 0.1520740 


s: 138 
logit 138 : -0.3521724 
logit mean 138 : -0.4277032 
logit RMSE 138 : 0.07184297 

boosting 138 : -0.7255712 
boosting mean 138 : -0.498161 
boosting RMSE 138 : 0.15452 

forest 138 : -0.4130446 
forest mean 138 : -0.3805927 
forest RMSE 138 : 0.05529587 

nnet 138 : -0.1220145 
nnet mean 138 : -0.4311478 
nnet RMSE 138 : 0.1533587 


s: 139 
logit 139 : -0.3433476 
logit mean 139 : -0.4270963 
logit RMSE 139 : 0.07174518 

boosting 139 : -0.5028203 
boosting mean 139 : -0.4981945 
boosting RMSE 139 : 0.1542100 

forest 139 : -0.407721 
forest mean 139 : -0.3807879 
forest RMSE 139 : 0.0551005 

nnet 139 : -0.6153963 
nnet mean 139 : -0.4324733 
nnet RMSE 139 : 0.1538943 


s: 140 
logit 140 : -0.4652387 
logit mean 140 : -0.4273687 
logit RMSE 140 : 0.0717008 

boosting 140 : -0.5256262 
boosting mean 140 : -0.4983904 
boosting RMSE 140 : 0.1540246 

forest 140 : -0.4057965 
forest mean 140 : -0.3809665 
forest RMSE 140 : 0.05490554 

nnet 140 : -0.5990528 
nnet mean 140 : -0.4336632 
nnet RMSE 140 : 0.1542637 


s: 141 
logit 141 : -0.3978133 
logit mean 141 : -0.4271591 
logit RMSE 141 : 0.07144632 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 141 : -0.5070782 
boosting mean 141 : -0.498452 
boosting RMSE 141 : 0.1537422 

forest 141 : -0.427132 
forest mean 141 : -0.3812939 
forest RMSE 141 : 0.05475819 

nnet 141 : -0.3283565 
nnet mean 141 : -0.4329163 
nnet RMSE 141 : 0.1538341 


s: 142 
logit 142 : -0.4117975 
logit mean 142 : -0.4270509 
logit RMSE 142 : 0.07120119 

boosting 142 : -0.4075726 
boosting mean 142 : -0.4978121 
boosting RMSE 142 : 0.1532012 

forest 142 : -0.3395418 
forest mean 142 : -0.3809999 
forest RMSE 142 : 0.0548004 

nnet 142 : -0.4719057 
nnet mean 142 : -0.4331909 
nnet RMSE 142 : 0.1534102 


s: 143 
logit 143 : -0.4974589 
logit mean 143 : -0.4275433 
logit RMSE 143 : 0.07141834 

boosting 143 : -0.5187976 
boosting mean 143 : -0.4979588 
boosting RMSE 143 : 0.1529874 

forest 143 : -0.4005144 
forest mean 143 : -0.3811363 
forest RMSE 143 : 0.05460847 

nnet 143 : -0.1333968 
nnet mean 143 : -0.4310944 
nnet RMSE 143 : 0.1544900 


s: 144 
logit 144 : -0.4545703 
logit mean 144 : -0.427731 
logit RMSE 144 : 0.07131506 

boosting 144 : -0.7031964 
boosting mean 144 : -0.4993841 
boosting RMSE 144 : 0.1545348 

forest 144 : -0.4002879 
forest mean 144 : -0.3812693 
forest RMSE 144 : 0.05441853 

nnet 144 : -0.722903 
nnet mean 144 : -0.4331209 
nnet RMSE 144 : 0.1562865 


s: 145 
logit 145 : -0.5183205 
logit mean 145 : -0.4283558 
logit RMSE 145 : 0.07174478 

boosting 145 : -0.5274512 
boosting mean 145 : -0.4995776 
boosting RMSE 145 : 0.1543643 

forest 145 : -0.3946362 
forest mean 145 : -0.3813615 
forest RMSE 145 : 0.05423239 

nnet 145 : -0.4862418 
nnet mean 145 : -0.4334872 
nnet RMSE 145 : 0.1559113 


s: 146 
logit 146 : -0.4140259 
logit mean 146 : -0.4282576 
logit RMSE 146 : 0.07150808 

boosting 146 : -0.5534383 
boosting mean 146 : -0.4999465 
boosting RMSE 146 : 0.154358 

forest 146 : -0.3356124 
forest mean 146 : -0.3810482 
forest RMSE 146 : 0.0543084 

nnet 146 : -0.1160682 
nnet mean 146 : -0.4313131 
nnet RMSE 146 : 0.1571433 


s: 147 
logit 147 : -0.48232 
logit mean 147 : -0.4286254 
logit RMSE 147 : 0.07158714 

boosting 147 : -0.5284779 
boosting mean 147 : -0.5001406 
boosting RMSE 147 : 0.1541966 

forest 147 : -0.3928814 
forest mean 147 : -0.3811287 
forest RMSE 147 : 0.05412655 

nnet 147 : -0.620649 
nnet mean 147 : -0.4326011 
nnet RMSE 147 : 0.1576617 


s: 148 
logit 148 : -0.3373892 
logit mean 148 : -0.4280089 
logit RMSE 148 : 0.07153027 

boosting 148 : -0.4499895 
boosting mean 148 : -0.4998018 
boosting RMSE 148 : 0.1537297 

forest 148 : -0.2985848 
forest mean 148 : -0.3805709 
forest RMSE 148 : 0.05458371 

nnet 148 : -0.4300205 
nnet mean 148 : -0.4325837 
nnet RMSE 148 : 0.1571475 


s: 149 
logit 149 : -0.522588 
logit mean 149 : -0.4286437 
logit RMSE 149 : 0.07199374 

boosting 149 : -0.4243339 
boosting mean 149 : -0.4992953 
boosting RMSE 149 : 0.1532260 

forest 149 : -0.3262088 
forest mean 149 : -0.3802061 
forest RMSE 149 : 0.0547351 

nnet 149 : 0.0986068 
nnet mean 149 : -0.4290187 
nnet RMSE 149 : 0.1618583 


s: 150 
logit 150 : -0.452763 
logit mean 150 : -0.4288045 
logit RMSE 150 : 0.07188257 

boosting 150 : -0.3258434 
boosting mean 150 : -0.4981389 
boosting RMSE 150 : 0.1528343 

forest 150 : -0.3591422 
forest mean 150 : -0.3800657 
forest RMSE 150 : 0.05465425 

nnet 150 : -0.4644379 
nnet mean 150 : -0.4292548 
nnet RMSE 150 : 0.1614037 


s: 151 
logit 151 : -0.4142823 
logit mean 151 : -0.4287083 
logit RMSE 151 : 0.07165358 

boosting 151 : -0.6820593 
boosting mean 151 : -0.4993569 
boosting RMSE 151 : 0.1540471 

forest 151 : -0.4341899 
forest mean 151 : -0.3804241 
forest RMSE 151 : 0.05454398 

nnet 151 : -0.6833124 
nnet mean 151 : -0.4309373 
nnet RMSE 151 : 0.1625121 


s: 152 
logit 152 : -0.5530257 
logit mean 152 : -0.4295262 
logit RMSE 152 : 0.07248804 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 152 : -0.5194556 
boosting mean 152 : -0.4994892 
boosting RMSE 152 : 0.1538450 

forest 152 : -0.3668808 
forest mean 152 : -0.380335 
forest RMSE 152 : 0.0544306 

nnet 152 : -0.839514 
nnet mean 152 : -0.4336253 
nnet RMSE 152 : 0.1658533 


s: 153 
logit 153 : -0.4675161 
logit mean 153 : -0.4297745 
logit RMSE 153 : 0.07245665 

boosting 153 : -0.5518297 
boosting mean 153 : -0.4998313 
boosting RMSE 153 : 0.1538319 

forest 153 : -0.422767 
forest mean 153 : -0.3806123 
forest RMSE 153 : 0.05428364 

nnet 153 : -0.4179394 
nnet mean 153 : -0.4335228 
nnet RMSE 153 : 0.1653167 


s: 154 
logit 154 : -0.4582639 
logit mean 154 : -0.4299595 
logit RMSE 154 : 0.07237347 

boosting 154 : -0.4570326 
boosting mean 154 : -0.4995534 
boosting RMSE 154 : 0.1534005 

forest 154 : -0.3644787 
forest mean 154 : -0.3805076 
forest RMSE 154 : 0.05418277 

nnet 154 : -0.4249990 
nnet mean 154 : -0.4334674 
nnet RMSE 154 : 0.1647914 


s: 155 
logit 155 : -0.4979316 
logit mean 155 : -0.430398 
logit RMSE 155 : 0.07256722 

boosting 155 : -0.547055 
boosting mean 155 : -0.4998598 
boosting RMSE 155 : 0.1533604 

forest 155 : -0.3361409 
forest mean 155 : -0.3802213 
forest RMSE 155 : 0.05425073 

nnet 155 : -0.3642531 
nnet mean 155 : -0.4330209 
nnet RMSE 155 : 0.1642841 


s: 156 
logit 156 : -0.4263231 
logit mean 156 : -0.4303719 
logit RMSE 156 : 0.07236495 

boosting 156 : -0.5679161 
boosting mean 156 : -0.5002961 
boosting RMSE 156 : 0.1534581 

forest 156 : -0.3380119 
forest mean 156 : -0.3799508 
forest RMSE 156 : 0.05430384 

nnet 156 : -0.3772328 
nnet mean 156 : -0.4326633 
nnet RMSE 156 : 0.1637668 


s: 157 
logit 157 : -0.4158011 
logit mean 157 : -0.4302791 
logit RMSE 157 : 0.07214514 

boosting 157 : -0.5837258 
boosting mean 157 : -0.5008275 
boosting RMSE 157 : 0.1536697 

forest 157 : -0.3219444 
forest mean 157 : -0.3795813 
forest RMSE 157 : 0.0544879 

nnet 157 : -0.5673986 
nnet mean 157 : -0.4335215 
nnet RMSE 157 : 0.1637902 


s: 158 
logit 158 : -0.4311295 
logit mean 158 : -0.4302845 
logit RMSE 158 : 0.0719591 

boosting 158 : -0.6390805 
boosting mean 158 : -0.5017025 
boosting RMSE 158 : 0.1543590 

forest 158 : -0.3808599 
forest mean 158 : -0.3795894 
forest RMSE 158 : 0.05433653 

nnet 158 : -0.2802668 
nnet mean 158 : -0.4325515 
nnet RMSE 158 : 0.1635487 


s: 159 
logit 159 : -0.4834584 
logit mean 159 : -0.4306189 
logit RMSE 159 : 0.07203716 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 159 : -0.4101564 
boosting mean 159 : -0.5011267 
boosting RMSE 159 : 0.1538749 

forest 159 : -0.3890942 
forest mean 159 : -0.3796492 
forest RMSE 159 : 0.0541723 

nnet 159 : -0.3003912 
nnet mean 159 : -0.4317203 
nnet RMSE 159 : 0.1632249 


s: 160 
logit 160 : -0.4597276 
logit mean 160 : -0.4308008 
logit RMSE 160 : 0.07196677 

boosting 160 : -0.4541716 
boosting mean 160 : -0.5008333 
boosting RMSE 160 : 0.1534531 

forest 160 : -0.3628404 
forest mean 160 : -0.3795441 
forest RMSE 160 : 0.05408259 

nnet 160 : -0.4265644 
nnet mean 160 : -0.4316881 
nnet RMSE 160 : 0.1627275 


s: 161 
logit 161 : -0.4238149 
logit mean 161 : -0.4307574 
logit RMSE 161 : 0.07176747 

boosting 161 : -0.5062222 
boosting mean 161 : -0.5008667 
boosting RMSE 161 : 0.1532047 

forest 161 : -0.2668495 
forest mean 161 : -0.3788441 
forest RMSE 161 : 0.05492611 

nnet 161 : -0.3858261 
nnet mean 161 : -0.4314032 
nnet RMSE 161 : 0.1622252 


s: 162 
logit 162 : -0.3371672 
logit mean 162 : -0.4301797 
logit RMSE 162 : 0.07171573 

boosting 162 : -0.5362691 
boosting mean 162 : -0.5010853 
boosting RMSE 162 : 0.1531059 

forest 162 : -0.3918671 
forest mean 162 : -0.3789245 
forest RMSE 162 : 0.05476005 

nnet 162 : -0.3769932 
nnet mean 162 : -0.4310673 
nnet RMSE 162 : 0.1617339 


s: 163 
logit 163 : -0.3826065 
logit mean 163 : -0.4298878 
logit RMSE 163 : 0.07150838 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 163 : -0.4010688 
boosting mean 163 : -0.5004717 
boosting RMSE 163 : 0.1526355 

forest 163 : -0.4790236 
forest mean 163 : -0.3795386 
forest RMSE 163 : 0.05494159 

nnet 163 : -0.499505 
nnet mean 163 : -0.4314872 
nnet RMSE 163 : 0.1614252 


s: 164 
logit 164 : -0.4818535 
logit mean 164 : -0.4302047 
logit RMSE 164 : 0.07157599 

boosting 164 : -0.6757011 
boosting mean 164 : -0.5015401 
boosting RMSE 164 : 0.1536848 

forest 164 : -0.4127278 
forest mean 164 : -0.379741 
forest RMSE 164 : 0.05478284 

nnet 164 : -0.4370731 
nnet mean 164 : -0.4315213 
nnet RMSE 164 : 0.1609584 


s: 165 
logit 165 : -0.4103536 
logit mean 165 : -0.4300844 
logit RMSE 165 : 0.07136332 

boosting 165 : -0.2479046 
boosting mean 165 : -0.500003 
boosting RMSE 165 : 0.1536752 

forest 165 : -0.4086847 
forest mean 165 : -0.3799164 
forest RMSE 165 : 0.05462076 

nnet 165 : -0.2307761 
nnet mean 165 : -0.4303046 
nnet RMSE 165 : 0.1610097 


s: 166 
logit 166 : -0.4418444 
logit mean 166 : -0.4301552 
logit RMSE 166 : 0.07122213 

boosting 166 : -0.4410412 
boosting mean 166 : -0.4996478 
boosting RMSE 166 : 0.1532448 

forest 166 : -0.4035452 
forest mean 166 : -0.3800588 
forest RMSE 166 : 0.05445669 

nnet 166 : -0.436975 
nnet mean 166 : -0.4303448 
nnet RMSE 166 : 0.1605497 


s: 167 
logit 167 : -0.4500771 
logit mean 167 : -0.4302745 
logit RMSE 167 : 0.07111423 

boosting 167 : -0.6133814 
boosting mean 167 : -0.5003288 
boosting RMSE 167 : 0.1536749 

forest 167 : -0.3200863 
forest mean 167 : -0.3796997 
forest RMSE 167 : 0.05464443 

nnet 167 : -0.3855384 
nnet mean 167 : -0.4300765 
nnet RMSE 167 : 0.1600722 


s: 168 
logit 168 : -0.3726409 
logit mean 168 : -0.4299315 
logit RMSE 168 : 0.07093368 

boosting 168 : -0.4015332 
boosting mean 168 : -0.4997407 
boosting RMSE 168 : 0.1532169 

forest 168 : -0.4833674 
forest mean 168 : -0.3803167 
forest RMSE 168 : 0.05485991 

nnet 168 : -0.4190159 
nnet mean 168 : -0.4300107 
nnet RMSE 168 : 0.1596018 


s: 169 
logit 169 : -0.4723366 
logit mean 169 : -0.4301824 
logit RMSE 169 : 0.07094206 

boosting 169 : -0.4180835 
boosting mean 169 : -0.4992576 
boosting RMSE 169 : 0.1527693 

forest 169 : -0.3809536 
forest mean 169 : -0.3803205 
forest RMSE 169 : 0.05471698 

nnet 169 : -0.4475557 
nnet mean 169 : -0.4301145 
nnet RMSE 169 : 0.1591710 


s: 170 
logit 170 : -0.3751353 
logit mean 170 : -0.4298586 
logit RMSE 170 : 0.0707588 

boosting 170 : -0.5783623 
boosting mean 170 : -0.4997229 
boosting RMSE 170 : 0.1529323 

forest 170 : -0.34256 
forest mean 170 : -0.3800984 
forest RMSE 170 : 0.0547334 

nnet 170 : -0.1308438 
nnet mean 170 : -0.4283541 
nnet RMSE 170 : 0.1600391 


s: 171 
logit 171 : -0.2854281 
logit mean 171 : -0.429014 
logit RMSE 171 : 0.07109355 

boosting 171 : -0.2853535 
boosting mean 171 : -0.4984693 
boosting RMSE 171 : 0.1527364 

forest 171 : -0.3327932 
forest mean 171 : -0.3798217 
forest RMSE 171 : 0.05481459 

nnet 171 : -0.2491583 
nnet mean 171 : -0.4273062 
nnet RMSE 171 : 0.1599868 


s: 172 
logit 172 : -0.3639462 
logit mean 172 : -0.4286357 
logit RMSE 172 : 0.07093987 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 172 : -0.5626802 
boosting mean 172 : -0.4988426 
boosting RMSE 172 : 0.1527960 

forest 172 : -0.3854816 
forest mean 172 : -0.3798546 
forest RMSE 172 : 0.05466623 

nnet 172 : -0.3982814 
nnet mean 172 : -0.4271374 
nnet RMSE 172 : 0.1595211 


s: 173 
logit 173 : -0.3931803 
logit mean 173 : -0.4284307 
logit RMSE 173 : 0.07073644 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 173 : -0.3670547 
boosting mean 173 : -0.4980808 
boosting RMSE 173 : 0.1523744 

forest 173 : -0.3314724 
forest mean 173 : -0.379575 
forest RMSE 173 : 0.05475643 

nnet 173 : -0.1401668 
nnet mean 173 : -0.4254786 
nnet RMSE 173 : 0.1602815 


s: 174 
logit 174 : -0.3634941 
logit mean 174 : -0.4280575 
logit RMSE 174 : 0.07058716 

boosting 174 : -0.326868 
boosting mean 174 : -0.4970968 
boosting RMSE 174 : 0.152037 

forest 174 : -0.3113380 
forest mean 174 : -0.3791828 
forest RMSE 174 : 0.05501103 

nnet 174 : -0.5505974 
nnet mean 174 : -0.4261977 
nnet RMSE 174 : 0.1602275 


s: 175 
logit 175 : -0.3633875 
logit mean 175 : -0.427688 
logit RMSE 175 : 0.07043958 

boosting 175 : -0.2884218 
boosting mean 175 : -0.4959044 
boosting RMSE 175 : 0.1518364 

forest 175 : -0.3372649 
forest mean 175 : -0.3789433 
forest RMSE 175 : 0.05505825 

nnet 175 : -0.4051921 
nnet mean 175 : -0.4260777 
nnet RMSE 175 : 0.1597695 


s: 176 
logit 176 : -0.4558101 
logit mean 176 : -0.4278478 
logit RMSE 176 : 0.07036505 

boosting 176 : -0.6816847 
boosting mean 176 : -0.49696 
boosting RMSE 176 : 0.1528861 

forest 176 : -0.3763206 
forest mean 176 : -0.3789284 
forest RMSE 176 : 0.05493061 

nnet 176 : -0.2482214 
nnet mean 176 : -0.4250671 
nnet RMSE 176 : 0.1597253 


s: 177 
logit 177 : -0.4101885 
logit mean 177 : -0.427748 
logit RMSE 177 : 0.07017018 

boosting 177 : -0.5454937 
boosting mean 177 : -0.4972342 
boosting RMSE 177 : 0.1528453 

forest 177 : -0.4003561 
forest mean 177 : -0.3790494 
forest RMSE 177 : 0.05477523 

nnet 177 : -0.4902847 
nnet mean 177 : -0.4254356 
nnet RMSE 177 : 0.1594179 


s: 178 
logit 178 : -0.5133315 
logit mean 178 : -0.4282288 
logit RMSE 178 : 0.07048652 

boosting 178 : -0.628376 
boosting mean 178 : -0.4979709 
boosting RMSE 178 : 0.1533736 

forest 178 : -0.3976812 
forest mean 178 : -0.3791541 
forest RMSE 178 : 0.05462143 

nnet 178 : -0.5789206 
nnet mean 178 : -0.4262978 
nnet RMSE 178 : 0.1595341 


s: 179 
logit 179 : -0.352949 
logit mean 179 : -0.4278082 
logit RMSE 179 : 0.07037728 

boosting 179 : -0.5011238 
boosting mean 179 : -0.4979885 
boosting RMSE 179 : 0.1531312 

forest 179 : -0.3759117 
forest mean 179 : -0.379136 
forest RMSE 179 : 0.05449839 

nnet 179 : -0.3183821 
nnet mean 179 : -0.425695 
nnet RMSE 179 : 0.1592048 


s: 180 
logit 180 : -0.4223435 
logit mean 180 : -0.4277779 
logit RMSE 180 : 0.07020127 

boosting 180 : -0.4435691 
boosting mean 180 : -0.4976862 
boosting RMSE 180 : 0.1527398 

forest 180 : -0.3739465 
forest mean 180 : -0.3791072 
forest RMSE 180 : 0.05438148 

nnet 180 : -0.3150847 
nnet mean 180 : -0.4250805 
nnet RMSE 180 : 0.1588881 


s: 181 
logit 181 : -0.4294814 
logit mean 181 : -0.4277873 
logit RMSE 181 : 0.07004136 

boosting 181 : -0.3105108 
boosting mean 181 : -0.4966521 
boosting RMSE 181 : 0.1524624 

forest 181 : -0.3578398 
forest mean 181 : -0.3789897 
forest RMSE 181 : 0.05432151 

nnet 181 : -0.4096795 
nnet mean 181 : -0.4249954 
nnet RMSE 181 : 0.1584502 


s: 182 
logit 182 : -0.5336582 
logit mean 182 : -0.428369 
logit RMSE 182 : 0.07054781 

boosting 182 : -0.7968419 
boosting mean 182 : -0.4983015 
boosting RMSE 182 : 0.1548624 

forest 182 : -0.2974987 
forest mean 182 : -0.3785419 
forest RMSE 182 : 0.0547023 

nnet 182 : -0.3581142 
nnet mean 182 : -0.4246279 
nnet RMSE 182 : 0.1580448 


s: 183 
logit 183 : -0.3836154 
logit mean 183 : -0.4281244 
logit RMSE 183 : 0.07036522 

boosting 183 : -0.39733 
boosting mean 183 : -0.4977497 
boosting RMSE 183 : 0.1544388 

forest 183 : -0.3669522 
forest mean 183 : -0.3784786 
forest RMSE 183 : 0.0546073 

nnet 183 : -0.4382914 
nnet mean 183 : -0.4247026 
nnet RMSE 183 : 0.1576378 


s: 184 
logit 184 : -0.3576599 
logit mean 184 : -0.4277415 
logit RMSE 184 : 0.07024313 

boosting 184 : -0.4566258 
boosting mean 184 : -0.4975262 
boosting RMSE 184 : 0.1540751 

forest 184 : -0.3474438 
forest mean 184 : -0.3783099 
forest RMSE 184 : 0.05459636 

nnet 184 : -0.4635113 
nnet mean 184 : -0.4249135 
nnet RMSE 184 : 0.1572785 


s: 185 
logit 185 : -0.4819447 
logit mean 185 : -0.4280345 
logit RMSE 185 : 0.07031162 

boosting 185 : -0.7159691 
boosting mean 185 : -0.498707 
boosting RMSE 185 : 0.1554043 

forest 185 : -0.3027317 
forest mean 185 : -0.3779014 
forest RMSE 185 : 0.05491623 

nnet 185 : -0.3773571 
nnet mean 185 : -0.4246564 
nnet RMSE 185 : 0.1568617 


s: 186 
logit 186 : -0.4318119 
logit mean 186 : -0.4280548 
logit RMSE 186 : 0.07016114 

boosting 186 : -0.5846105 
boosting mean 186 : -0.4991688 
boosting RMSE 186 : 0.1555760 

forest 186 : -0.3335773 
forest mean 186 : -0.3776631 
forest RMSE 186 : 0.05498453 

nnet 186 : -0.6513001 
nnet mean 186 : -0.4258749 
nnet RMSE 186 : 0.1575209 


s: 187 
logit 187 : -0.4802809 
logit mean 187 : -0.4283341 
logit RMSE 187 : 0.07021914 

boosting 187 : -0.3296783 
boosting mean 187 : -0.4982625 
boosting RMSE 187 : 0.1552446 

forest 187 : -0.4546111 
forest mean 187 : -0.3780746 
forest RMSE 187 : 0.05498254 

nnet 187 : -0.3589677 
nnet mean 187 : -0.4255171 
nnet RMSE 187 : 0.1571278 


s: 188 
logit 188 : -0.4392677 
logit mean 188 : -0.4283922 
logit RMSE 188 : 0.07009067 

boosting 188 : -0.4006922 
boosting mean 188 : -0.4977435 
boosting RMSE 188 : 0.1548312 

forest 188 : -0.2792816 
forest mean 188 : -0.3775491 
forest RMSE 188 : 0.05553841 

nnet 188 : -0.3606044 
nnet mean 188 : -0.4251719 
nnet RMSE 188 : 0.1567357 


s: 189 
logit 189 : -0.3474552 
logit mean 189 : -0.427964 
logit RMSE 189 : 0.0700094 

boosting 189 : -0.6681826 
boosting mean 189 : -0.4986453 
boosting RMSE 189 : 0.1556483 

forest 189 : -0.3483611 
forest mean 189 : -0.3773946 
forest RMSE 189 : 0.0555185 

nnet 189 : -0.5403256 
nnet mean 189 : -0.4257811 
nnet RMSE 189 : 0.1566534 


s: 190 
logit 190 : -0.4402822 
logit mean 190 : -0.4280288 
logit RMSE 190 : 0.06988606 

boosting 190 : -0.4799126 
boosting mean 190 : -0.4985467 
boosting RMSE 190 : 0.1553464 

forest 190 : -0.5184794 
forest mean 190 : -0.3781372 
forest RMSE 190 : 0.05603536 

nnet 190 : -0.4844692 
nnet mean 190 : -0.42609 
nnet RMSE 190 : 0.1563608 


s: 191 
logit 191 : -0.4465691 
logit mean 191 : -0.4281259 
logit RMSE 191 : 0.06978427 

boosting 191 : -0.477458 
boosting mean 191 : -0.4984363 
boosting RMSE 191 : 0.1550405 

forest 191 : -0.4040504 
forest mean 191 : -0.3782729 
forest RMSE 191 : 0.05588925 

nnet 191 : -0.5946956 
nnet mean 191 : -0.4269728 
nnet RMSE 191 : 0.1565859 


s: 192 
logit 192 : -0.5015428 
logit mean 192 : -0.4285083 
logit RMSE 192 : 0.06998702 

boosting 192 : -0.7006135 
boosting mean 192 : -0.4994893 
boosting RMSE 192 : 0.1561507 

forest 192 : -0.4128621 
forest mean 192 : -0.378453 
forest RMSE 192 : 0.05575124 

nnet 192 : -0.5996835 
nnet mean 192 : -0.4278723 
nnet RMSE 192 : 0.1568410 


s: 193 
logit 193 : -0.4477113 
logit mean 193 : -0.4286078 
logit RMSE 193 : 0.0698899 

boosting 193 : -0.5742027 
boosting mean 193 : -0.4998764 
boosting RMSE 193 : 0.1562496 

forest 193 : -0.4355072 
forest mean 193 : -0.3787486 
forest RMSE 193 : 0.05566533 

nnet 193 : -0.3653128 
nnet mean 193 : -0.4275482 
nnet RMSE 193 : 0.1564541 


s: 194 
logit 194 : -0.4144916 
logit mean 194 : -0.428535 
logit RMSE 194 : 0.0697173 

boosting 194 : -0.4826162 
boosting mean 194 : -0.4997874 
boosting RMSE 194 : 0.1559592 

forest 194 : -0.4229662 
forest mean 194 : -0.3789766 
forest RMSE 194 : 0.05554615 

nnet 194 : -0.4510384 
nnet mean 194 : -0.4276692 
nnet RMSE 194 : 0.1560934 


s: 195 
logit 195 : -0.4334941 
logit mean 195 : -0.4285604 
logit RMSE 195 : 0.06957967 

boosting 195 : -0.7603325 
boosting mean 195 : -0.5011235 
boosting RMSE 195 : 0.1576844 

forest 195 : -0.394135 
forest mean 195 : -0.3790543 
forest RMSE 195 : 0.05540514 

nnet 195 : -0.4450315 
nnet mean 195 : -0.4277583 
nnet RMSE 195 : 0.1557260 


s: 196 
logit 196 : -0.427983 
logit mean 196 : -0.4285575 
logit RMSE 196 : 0.06943072 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 196 : -0.4153403 
boosting mean 196 : -0.5006859 
boosting RMSE 196 : 0.1572855 

forest 196 : -0.3390841 
forest mean 196 : -0.3788504 
forest RMSE 196 : 0.05543464 

nnet 196 : -0.4443810 
nnet mean 196 : -0.4278431 
nnet RMSE 196 : 0.1553606 


s: 197 
logit 197 : -0.4821427 
logit mean 197 : -0.4288295 
logit RMSE 197 : 0.06950112 

boosting 197 : -0.6076744 
boosting mean 197 : -0.501229 
boosting RMSE 197 : 0.1575820 

forest 197 : -0.4194400 
forest mean 197 : -0.3790564 
forest RMSE 197 : 0.05531111 

nnet 197 : -0.4381169 
nnet mean 197 : -0.4278952 
nnet RMSE 197 : 0.1549896 


s: 198 
logit 198 : -0.4675353 
logit mean 198 : -0.429025 
logit RMSE 198 : 0.06949133 

boosting 198 : -0.5477132 
boosting mean 198 : -0.5014637 
boosting RMSE 198 : 0.1575337 

forest 198 : -0.356172 
forest mean 198 : -0.3789408 
forest RMSE 198 : 0.05525911 

nnet 198 : -0.3922818 
nnet mean 198 : -0.4277154 
nnet RMSE 198 : 0.1545987 


s: 199 
logit 199 : -0.3877830 
logit mean 199 : -0.4288177 
logit RMSE 199 : 0.06932192 

boosting 199 : -0.3191271 
boosting mean 199 : -0.5005475 
boosting RMSE 199 : 0.1572419 

forest 199 : -0.3778226 
forest mean 199 : -0.3789352 
forest RMSE 199 : 0.05514251 

nnet 199 : -0.4444474 
nnet mean 199 : -0.4277995 
nnet RMSE 199 : 0.1542419 


s: 200 
logit 200 : -0.3664464 
logit mean 200 : -0.4285059 
logit RMSE 200 : 0.06918909 

boosting 200 : -0.3742921 
boosting mean 200 : -0.4999162 
boosting RMSE 200 : 0.1568588 

forest 200 : -0.3835289 
forest mean 200 : -0.3789582 
forest RMSE 200 : 0.05501681 

nnet 200 : -0.4094328 
nnet mean 200 : -0.4277076 
nnet RMSE 200 : 0.1538573 


s: 201 
logit 201 : -0.4496306 
logit mean 201 : -0.428611 
logit RMSE 201 : 0.06910549 

boosting 201 : -0.33247 
boosting mean 201 : -0.4990831 
boosting RMSE 201 : 0.1565406 

forest 201 : -0.3591839 
forest mean 201 : -0.3788598 
forest RMSE 201 : 0.05495524 

nnet 201 : -0.2187511 
nnet mean 201 : -0.426668 
nnet RMSE 201 : 0.1540056 


s: 202 
logit 202 : -0.3753536 
logit mean 202 : -0.4283473 
logit RMSE 202 : 0.06895603 

boosting 202 : -0.6635602 
boosting mean 202 : -0.4998974 
boosting RMSE 202 : 0.1572499 

forest 202 : -0.4063731 
forest mean 202 : -0.378996 
forest RMSE 202 : 0.05482088 

nnet 202 : -0.4357991 
nnet mean 202 : -0.4267132 
nnet RMSE 202 : 0.1536446 


s: 203 
logit 203 : -0.462692 
logit mean 203 : -0.4285165 
logit RMSE 203 : 0.06892657 

boosting 203 : -0.4583923 
boosting mean 203 : -0.4996929 
boosting RMSE 203 : 0.1569157 

forest 203 : -0.4432616 
forest mean 203 : -0.3793126 
forest RMSE 203 : 0.05476992 

nnet 203 : -0.4914906 
nnet mean 203 : -0.4270323 
nnet RMSE 203 : 0.1534001 


s: 204 
logit 204 : -0.3592518 
logit mean 204 : -0.428177 
logit RMSE 204 : 0.06881658 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 204 : -0.3322115 
boosting mean 204 : -0.4988719 
boosting RMSE 204 : 0.1566025 

forest 204 : -0.2782347 
forest mean 204 : -0.3788171 
forest RMSE 204 : 0.05529665 

nnet 204 : -0.3283501 
nnet mean 204 : -0.4265486 
nnet RMSE 204 : 0.1531059 


s: 205 
logit 205 : -0.4263195 
logit mean 205 : -0.4281679 
logit RMSE 205 : 0.06867314 

boosting 205 : -0.8639488 
boosting mean 205 : -0.5006528 
boosting RMSE 205 : 0.1595453 

forest 205 : -0.4014646 
forest mean 205 : -0.3789276 
forest RMSE 205 : 0.05516171 

nnet 205 : -0.5515506 
nnet mean 205 : -0.4271584 
nnet RMSE 205 : 0.1530984 


s: 206 
logit 206 : -0.4481855 
logit mean 206 : -0.4282651 
logit RMSE 206 : 0.06858847 

boosting 206 : -0.6323789 
boosting mean 206 : -0.5012922 
boosting RMSE 206 : 0.159979 

forest 206 : -0.4246522 
forest mean 206 : -0.3791495 
forest RMSE 206 : 0.05505446 

nnet 206 : -0.3472721 
nnet mean 206 : -0.4267706 
nnet RMSE 206 : 0.1527705 


s: 207 
logit 207 : -0.3816888 
logit mean 207 : -0.4280401 
logit RMSE 207 : 0.06843443 

boosting 207 : -0.5091683 
boosting mean 207 : -0.5013303 
boosting RMSE 207 : 0.1597724 

forest 207 : -0.4455255 
forest mean 207 : -0.3794702 
forest RMSE 207 : 0.05501239 

nnet 207 : -0.4221644 
nnet mean 207 : -0.4267483 
nnet RMSE 207 : 0.1524088 


s: 208 
logit 208 : -0.3751236 
logit mean 208 : -0.4277857 
logit RMSE 208 : 0.06829151 

boosting 208 : -0.5100599 
boosting mean 208 : -0.5013723 
boosting RMSE 208 : 0.1595704 

forest 208 : -0.3543235 
forest mean 208 : -0.3793493 
forest RMSE 208 : 0.0549713 

nnet 208 : -0.3383515 
nnet mean 208 : -0.4263233 
nnet RMSE 208 : 0.1521021 


s: 209 
logit 209 : -0.4142958 
logit mean 209 : -0.4277211 
logit RMSE 209 : 0.06813512 

boosting 209 : -0.4210077 
boosting mean 209 : -0.5009877 
boosting RMSE 209 : 0.1591949 

forest 209 : -0.3837376 
forest mean 209 : -0.3793703 
forest RMSE 209 : 0.05485117 

nnet 209 : -0.6291718 
nnet mean 209 : -0.4272939 
nnet RMSE 209 : 0.1525636 


s: 210 
logit 210 : -0.6704145 
logit mean 210 : -0.4288768 
logit RMSE 210 : 0.07048757 

boosting 210 : -0.596699 
boosting mean 210 : -0.5014435 
boosting RMSE 210 : 0.1593944 

forest 210 : -0.382175 
forest mean 210 : -0.3793837 
forest RMSE 210 : 0.05473424 

nnet 210 : -0.4227431 
nnet mean 210 : -0.4272722 
nnet RMSE 210 : 0.1522080 


s: 211 
logit 211 : -0.4870355 
logit mean 211 : -0.4291524 
logit RMSE 211 : 0.07057515 

boosting 211 : -0.4835179 
boosting mean 211 : -0.5013585 
boosting RMSE 211 : 0.1591201 

forest 211 : -0.3862586 
forest mean 211 : -0.3794162 
forest RMSE 211 : 0.05461258 

nnet 211 : -0.6132994 
nnet mean 211 : -0.4281539 
nnet RMSE 211 : 0.1525552 


s: 212 
logit 212 : -0.3775032 
logit mean 212 : -0.4289088 
logit RMSE 212 : 0.07042545 

boosting 212 : -0.6523885 
boosting mean 212 : -0.502071 
boosting RMSE 212 : 0.159688 

forest 212 : -0.3995087 
forest mean 212 : -0.379511 
forest RMSE 212 : 0.05448363 

nnet 212 : -0.561676 
nnet mean 212 : -0.4287837 
nnet RMSE 212 : 0.1525995 


s: 213 
logit 213 : -0.4537184 
logit mean 213 : -0.4290253 
logit RMSE 213 : 0.07035628 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 213 : -0.5034838 
boosting mean 213 : -0.5020776 
boosting RMSE 213 : 0.1594704 

forest 213 : -0.3965055 
forest mean 213 : -0.3795908 
forest RMSE 213 : 0.05435611 

nnet 213 : -0.2330785 
nnet mean 213 : -0.4278649 
nnet RMSE 213 : 0.1526699 


s: 214 
logit 214 : -0.427612 
logit mean 214 : -0.4290187 
logit RMSE 214 : 0.07021708 

boosting 214 : -0.5686992 
boosting mean 214 : -0.5023889 
boosting RMSE 214 : 0.1595148 

forest 214 : -0.4225515 
forest mean 214 : -0.3797915 
forest RMSE 214 : 0.05425087 

nnet 214 : -0.2142371 
nnet mean 214 : -0.4268666 
nnet RMSE 214 : 0.1528412 


s: 215 
logit 215 : -0.4181852 
logit mean 215 : -0.4289683 
logit RMSE 215 : 0.07006457 

boosting 215 : -0.2247616 
boosting mean 215 : -0.5010976 
boosting RMSE 215 : 0.1595915 

forest 215 : -0.2880894 
forest mean 215 : -0.379365 
forest RMSE 215 : 0.05466003 

nnet 215 : -0.3030363 
nnet mean 215 : -0.4262907 
nnet RMSE 215 : 0.1526287 


s: 216 
logit 216 : -0.4577032 
logit mean 216 : -0.4291013 
logit RMSE 216 : 0.07001237 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 216 : -0.5905771 
boosting mean 216 : -0.5015119 
boosting RMSE 216 : 0.1597488 

forest 216 : -0.4353328 
forest mean 216 : -0.3796241 
forest RMSE 216 : 0.05458632 

nnet 216 : -0.7431558 
nnet mean 216 : -0.4277577 
nnet RMSE 216 : 0.1540546 


s: 217 
logit 217 : -0.3968907 
logit mean 217 : -0.4289529 
logit RMSE 217 : 0.06985119 

boosting 217 : -0.3087643 
boosting mean 217 : -0.5006236 
boosting RMSE 217 : 0.1595006 

forest 217 : -0.312379 
forest mean 217 : -0.3793143 
forest RMSE 217 : 0.05478426 

nnet 217 : -0.4641775 
nnet mean 217 : -0.4279255 
nnet RMSE 217 : 0.1537610 


s: 218 
logit 218 : -0.2968553 
logit mean 218 : -0.4283469 
logit RMSE 218 : 0.07004005 

boosting 218 : -0.1350873 
boosting mean 218 : -0.4989469 
boosting RMSE 218 : 0.1601426 

forest 218 : -0.3437055 
forest mean 218 : -0.3791509 
forest RMSE 218 : 0.05479129 

nnet 218 : -0.5263708 
nnet mean 218 : -0.4283771 
nnet RMSE 218 : 0.1536465 


s: 219 
logit 219 : -0.4904067 
logit mean 219 : -0.4286303 
logit RMSE 219 : 0.07014649 

boosting 219 : -0.5621456 
boosting mean 219 : -0.4992354 
boosting RMSE 219 : 0.1601518 

forest 219 : -0.3042507 
forest mean 219 : -0.3788089 
forest RMSE 219 : 0.05504761 

nnet 219 : -0.1484731 
nnet mean 219 : -0.427099 
nnet RMSE 219 : 0.1542347 


s: 220 
logit 220 : -0.4144514 
logit mean 220 : -0.4285659 
logit RMSE 220 : 0.06999366 

boosting 220 : -0.3843416 
boosting mean 220 : -0.4987132 
boosting RMSE 220 : 0.1597909 

forest 220 : -0.3915753 
forest mean 220 : -0.3788669 
forest RMSE 220 : 0.0549253 

nnet 220 : -0.3947525 
nnet mean 220 : -0.4269519 
nnet RMSE 220 : 0.1538841 


s: 221 
logit 221 : -0.4379391 
logit mean 221 : -0.4286083 
logit RMSE 221 : 0.06988174 

boosting 221 : -0.6208952 
boosting mean 221 : -0.4992661 
boosting RMSE 221 : 0.1601199 

forest 221 : -0.4237971 
forest mean 221 : -0.3790702 
forest RMSE 221 : 0.05482427 

nnet 221 : -0.6541069 
nnet mean 221 : -0.4279798 
nnet RMSE 221 : 0.1544841 


s: 222 
logit 222 : -0.3928736 
logit mean 222 : -0.4284473 
logit RMSE 222 : 0.06972582 

boosting 222 : -0.5058286 
boosting mean 222 : -0.4992956 
boosting RMSE 222 : 0.1599167 

forest 222 : -0.3712397 
forest mean 222 : -0.3790350 
forest RMSE 222 : 0.0547347 

nnet 222 : -0.3468949 
nnet mean 222 : -0.4276145 
nnet RMSE 222 : 0.1541770 


s: 223 
logit 223 : -0.3534898 
logit mean 223 : -0.4281112 
logit RMSE 223 : 0.06963899 

boosting 223 : -0.4807794 
boosting mean 223 : -0.4992126 
boosting RMSE 223 : 0.1596494 

forest 223 : -0.3486927 
forest mean 223 : -0.3788989 
forest RMSE 223 : 0.0547198 

nnet 223 : -0.4054989 
nnet mean 223 : -0.4275154 
nnet RMSE 223 : 0.1538314 


s: 224 
logit 224 : -0.3731687 
logit mean 224 : -0.4278659 
logit RMSE 224 : 0.06950649 

boosting 224 : -0.3480087 
boosting mean 224 : -0.4985376 
boosting RMSE 224 : 0.1593305 

forest 224 : -0.3673748 
forest mean 224 : -0.3788474 
forest RMSE 224 : 0.05464102 

nnet 224 : -0.4841966 
nnet mean 224 : -0.4277684 
nnet RMSE 224 : 0.1535907 


s: 225 
logit 225 : -0.4990258 
logit mean 225 : -0.4281822 
logit RMSE 225 : 0.06966537 

boosting 225 : -0.732427 
boosting mean 225 : -0.4995771 
boosting RMSE 225 : 0.1605133 

forest 225 : -0.4626634 
forest mean 225 : -0.37922 
forest RMSE 225 : 0.05467928 

nnet 225 : -0.7413993 
nnet mean 225 : -0.4291623 
nnet RMSE 225 : 0.1549299 


s: 226 
logit 226 : -0.4861315 
logit mean 226 : -0.4284386 
logit RMSE 226 : 0.06974679 

boosting 226 : -0.4574454 
boosting mean 226 : -0.4993907 
boosting RMSE 226 : 0.1602034 

forest 226 : -0.4009755 
forest mean 226 : -0.3793162 
forest RMSE 226 : 0.05455822 

nnet 226 : -0.5068959 
nnet mean 226 : -0.4295063 
nnet RMSE 226 : 0.1547502 


s: 227 
logit 227 : -0.4322279 
logit mean 227 : -0.4284553 
logit RMSE 227 : 0.06962586 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 227 : -0.4989756 
boosting mean 227 : -0.4993888 
boosting RMSE 227 : 0.1599851 

forest 227 : -0.4461007 
forest mean 227 : -0.3796104 
forest RMSE 227 : 0.05452384 

nnet 227 : -0.7874163 
nnet mean 227 : -0.431083 
nnet RMSE 227 : 0.1565354 


s: 228 
logit 228 : -0.3581796 
logit mean 228 : -0.4281471 
logit RMSE 228 : 0.06952819 

boosting 228 : -0.4549334 
boosting mean 228 : -0.4991938 
boosting RMSE 228 : 0.1596753 

forest 228 : -0.3263168 
forest mean 228 : -0.3793767 
forest RMSE 228 : 0.05462254 

nnet 228 : -0.4317048 
nnet mean 228 : -0.4310857 
nnet RMSE 228 : 0.1562058 


s: 229 
logit 229 : -0.3239351 
logit mean 229 : -0.427692 
logit RMSE 229 : 0.06955807 

boosting 229 : -0.5788655 
boosting mean 229 : -0.4995418 
boosting RMSE 229 : 0.1597641 

forest 229 : -0.4160224 
forest mean 229 : -0.3795367 
forest RMSE 229 : 0.05451343 

nnet 229 : -0.526726 
nnet mean 229 : -0.4315033 
nnet RMSE 229 : 0.1560892 


s: 230 
logit 230 : -0.3711485 
logit mean 230 : -0.4274461 
logit RMSE 230 : 0.06943276 

boosting 230 : -0.4367597 
boosting mean 230 : -0.4992688 
boosting RMSE 230 : 0.1594348 

forest 230 : -0.3669911 
forest mean 230 : -0.3794822 
forest RMSE 230 : 0.05443832 

nnet 230 : -0.5758154 
nnet mean 230 : -0.4321308 
nnet RMSE 230 : 0.1561803 


s: 231 
logit 231 : -0.4925197 
logit mean 231 : -0.4277278 
logit RMSE 231 : 0.06954922 

boosting 231 : -0.454215 
boosting mean 231 : -0.4990737 
boosting RMSE 231 : 0.1591294 

forest 231 : -0.3692721 
forest mean 231 : -0.379438 
forest RMSE 231 : 0.05435797 

nnet 231 : -0.3655185 
nnet mean 231 : -0.4318424 
nnet RMSE 231 : 0.1558584 


s: 232 
logit 232 : -0.4379085 
logit mean 232 : -0.4277717 
logit RMSE 232 : 0.06944378 

boosting 232 : -0.1567065 
boosting mean 232 : -0.497598 
boosting RMSE 232 : 0.1595874 

forest 232 : -0.3448002 
forest mean 232 : -0.3792887 
forest RMSE 232 : 0.05436163 

nnet 232 : -0.3477953 
nnet mean 232 : -0.4314802 
nnet RMSE 232 : 0.1555599 


s: 233 
logit 233 : -0.4343453 
logit mean 233 : -0.4277999 
logit RMSE 233 : 0.06933112 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 233 : -0.2778490 
boosting mean 233 : -0.4966549 
boosting RMSE 233 : 0.1594455 

forest 233 : -0.4266083 
forest mean 233 : -0.3794918 
forest RMSE 233 : 0.05427285 

nnet 233 : -0.3485038 
nnet mean 233 : -0.431124 
nnet RMSE 233 : 0.1552624 


s: 234 
logit 234 : -0.4572242 
logit mean 234 : -0.4279257 
logit RMSE 234 : 0.06928388 

boosting 234 : -0.5357375 
boosting mean 234 : -0.4968219 
boosting RMSE 234 : 0.1593517 

forest 234 : -0.3891354 
forest mean 234 : -0.379533 
forest RMSE 234 : 0.05416142 

nnet 234 : -0.4065317 
nnet mean 234 : -0.4310189 
nnet RMSE 234 : 0.1549309 


s: 235 
logit 235 : -0.4728303 
logit mean 235 : -0.4281168 
logit RMSE 235 : 0.06929936 

boosting 235 : -0.4489263 
boosting mean 235 : -0.4966181 
boosting RMSE 235 : 0.1590443 

forest 235 : -0.3560532 
forest mean 235 : -0.3794331 
forest RMSE 235 : 0.05412203 

nnet 235 : -0.3022626 
nnet mean 235 : -0.430471 
nnet RMSE 235 : 0.1547323 


s: 236 
logit 236 : -0.5264978 
logit mean 236 : -0.4285336 
logit RMSE 236 : 0.0696409 

boosting 236 : -0.4046708 
boosting mean 236 : -0.4962285 
boosting RMSE 236 : 0.1587073 

forest 236 : -0.4238786 
forest mean 236 : -0.3796214 
forest RMSE 236 : 0.05402961 

nnet 236 : -0.3293804 
nnet mean 236 : -0.4300427 
nnet RMSE 236 : 0.1544726 


s: 237 
logit 237 : -0.3734615 
logit mean 237 : -0.4283013 
logit RMSE 237 : 0.0695152 

boosting 237 : -0.4567434 
boosting mean 237 : -0.4960619 
boosting RMSE 237 : 0.1584150 

forest 237 : -0.3429245 
forest mean 237 : -0.3794665 
forest RMSE 237 : 0.05404282 

nnet 237 : -0.4237607 
nnet mean 237 : -0.4300162 
nnet RMSE 237 : 0.1541540 


s: 238 
logit 238 : -0.454839 
logit mean 238 : -0.4284128 
logit RMSE 238 : 0.06946003 

boosting 238 : -0.3916775 
boosting mean 238 : -0.4956233 
boosting RMSE 238 : 0.1580828 

forest 238 : -0.3413724 
forest mean 238 : -0.3793065 
forest RMSE 238 : 0.0540629 

nnet 238 : -0.3997086 
nnet mean 238 : -0.4298888 
nnet RMSE 238 : 0.1538299 


s: 239 
logit 239 : -0.4347295 
logit mean 239 : -0.4284392 
logit RMSE 239 : 0.06935095 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 239 : -0.5274874 
boosting mean 239 : -0.4957566 
boosting RMSE 239 : 0.1579671 

forest 239 : -0.4563018 
forest mean 239 : -0.3796286 
forest RMSE 239 : 0.05407246 

nnet 239 : -0.2704259 
nnet mean 239 : -0.4292216 
nnet RMSE 239 : 0.1537363 


s: 240 
logit 240 : -0.4108916 
logit mean 240 : -0.4283661 
logit RMSE 240 : 0.06920989 

boosting 240 : -0.65949 
boosting mean 240 : -0.4964389 
boosting RMSE 240 : 0.1585251 

forest 240 : -0.4078122 
forest mean 240 : -0.3797461 
forest RMSE 240 : 0.05396205 

nnet 240 : -0.5131404 
nnet mean 240 : -0.4295713 
nnet RMSE 240 : 0.1535895 


s: 241 
logit 241 : -0.3915019 
logit mean 241 : -0.4282131 
logit RMSE 241 : 0.06906832 

boosting 241 : -0.3918681 
boosting mean 241 : -0.4960049 
boosting RMSE 241 : 0.1581967 

forest 241 : -0.3240315 
forest mean 241 : -0.3795149 
forest RMSE 241 : 0.05407187 

nnet 241 : -0.4576423 
nnet mean 241 : -0.4296878 
nnet RMSE 241 : 0.1533154 


s: 242 
logit 242 : -0.2822003 
logit mean 242 : -0.4276098 
logit RMSE 242 : 0.0693402 

boosting 242 : -0.491339 
boosting mean 242 : -0.4959857 
boosting RMSE 242 : 0.1579787 

forest 242 : -0.4035554 
forest mean 242 : -0.3796142 
forest RMSE 242 : 0.05396052 

nnet 242 : -0.6339798 
nnet mean 242 : -0.4305320 
nnet RMSE 242 : 0.1537359 


s: 243 
logit 243 : -0.3931747 
logit mean 243 : -0.4274681 
logit RMSE 243 : 0.06919876 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 243 : -0.6058793 
boosting mean 243 : -0.4964379 
boosting RMSE 243 : 0.1582055 

forest 243 : -0.3695865 
forest mean 243 : -0.379573 
forest RMSE 243 : 0.05388471 

nnet 243 : -0.7176937 
nnet mean 243 : -0.4317137 
nnet RMSE 243 : 0.1547669 


s: 244 
logit 244 : -0.4143009 
logit mean 244 : -0.4274141 
logit RMSE 244 : 0.06906288 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 244 : -0.4468692 
boosting mean 244 : -0.4962348 
boosting RMSE 244 : 0.1579095 

forest 244 : -0.3540713 
forest mean 244 : -0.3794684 
forest RMSE 244 : 0.0538545 

nnet 244 : -0.2375888 
nnet mean 244 : -0.4309181 
nnet RMSE 244 : 0.1547990 


s: 245 
logit 245 : -0.3675848 
logit mean 245 : -0.4271699 
logit RMSE 245 : 0.0689529 

boosting 245 : -0.5976931 
boosting mean 245 : -0.4966489 
boosting RMSE 245 : 0.1580922 

forest 245 : -0.3807976 
forest mean 245 : -0.3794739 
forest RMSE 245 : 0.05375848 

nnet 245 : -0.679777 
nnet mean 245 : -0.4319338 
nnet RMSE 245 : 0.1555134 


s: 246 
logit 246 : -0.4326243 
logit mean 246 : -0.4271921 
logit RMSE 246 : 0.06884404 

boosting 246 : -0.6612772 
boosting mean 246 : -0.4973181 
boosting RMSE 246 : 0.1586476 

forest 246 : -0.396365 
forest mean 246 : -0.3795425 
forest RMSE 246 : 0.0536496 

nnet 246 : -0.2867483 
nnet mean 246 : -0.4313437 
nnet RMSE 246 : 0.1553649 


s: 247 
logit 247 : -0.3807884 
logit mean 247 : -0.4270042 
logit RMSE 247 : 0.06871541 

boosting 247 : -0.4251097 
boosting mean 247 : -0.4970258 
boosting RMSE 247 : 0.1583342 

forest 247 : -0.4129297 
forest mean 247 : -0.3796777 
forest RMSE 247 : 0.05354721 

nnet 247 : -0.6024328 
nnet mean 247 : -0.4320363 
nnet RMSE 247 : 0.1555842 


s: 248 
logit 248 : -0.3303924 
logit mean 248 : -0.4266146 
logit RMSE 248 : 0.06871903 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 248 : -0.501541 
boosting mean 248 : -0.497044 
boosting RMSE 248 : 0.1581461 

forest 248 : -0.4071884 
forest mean 248 : -0.3797886 
forest RMSE 248 : 0.05344109 

nnet 248 : -0.4224101 
nnet mean 248 : -0.4319975 
nnet RMSE 248 : 0.1552767 


s: 249 
logit 249 : -0.3930839 
logit mean 249 : -0.42648 
logit RMSE 249 : 0.0685823 

boosting 249 : -0.4927036 
boosting mean 249 : -0.4970265 
boosting RMSE 249 : 0.1579375 

forest 249 : -0.3647936 
forest mean 249 : -0.3797284 
forest RMSE 249 : 0.05338032 

nnet 249 : -0.3714362 
nnet mean 249 : -0.4317543 
nnet RMSE 249 : 0.1549751 


s: 250 
logit 250 : -0.5293706 
logit mean 250 : -0.4268915 
logit RMSE 250 : 0.06893232 

boosting 250 : -0.6543915 
boosting mean 250 : -0.497656 
boosting RMSE 250 : 0.1584404 

forest 250 : -0.3891775 
forest mean 250 : -0.3797662 
forest RMSE 250 : 0.05327785 

nnet 250 : -0.2682855 
nnet mean 250 : -0.4311004 
nnet RMSE 250 : 0.1548891 


s: 251 
logit 251 : -0.3963484 
logit mean 251 : -0.4267698 
logit RMSE 251 : 0.06879526 

boosting 251 : -0.1881690 
boosting mean 251 : -0.496423 
boosting RMSE 251 : 0.1586887 

forest 251 : -0.4019365 
forest mean 251 : -0.3798545 
forest RMSE 251 : 0.05317175 

nnet 251 : -0.2810622 
nnet mean 251 : -0.4305027 
nnet RMSE 251 : 0.1547624 


s: 252 
logit 252 : -0.3438067 
logit mean 252 : -0.4264406 
logit RMSE 252 : 0.06874981 

boosting 252 : -0.7299569 
boosting mean 252 : -0.4973497 
boosting RMSE 252 : 0.1597317 

forest 252 : -0.3938028 
forest mean 252 : -0.3799099 
forest RMSE 252 : 0.05306759 

nnet 252 : -0.4147441 
nnet mean 252 : -0.4304401 
nnet RMSE 252 : 0.1544578 


s: 253 
logit 253 : -0.5230006 
logit mean 253 : -0.4268223 
logit RMSE 253 : 0.0690482 

boosting 253 : -0.750521 
boosting mean 253 : -0.4983504 
boosting RMSE 253 : 0.1609317 

forest 253 : -0.4098223 
forest mean 253 : -0.3800281 
forest RMSE 253 : 0.0529662 

nnet 253 : -0.4838069 
nnet mean 253 : -0.4306511 
nnet RMSE 253 : 0.1542423 


s: 254 
logit 254 : -0.3971278 
logit mean 254 : -0.4267054 
logit RMSE 254 : 0.06891238 

boosting 254 : -0.526135 
boosting mean 254 : -0.4984598 
boosting RMSE 254 : 0.1608094 

forest 254 : -0.4068052 
forest mean 254 : -0.3801335 
forest RMSE 254 : 0.05286356 

nnet 254 : -0.5445262 
nnet mean 254 : -0.4310994 
nnet RMSE 254 : 0.1542052 


s: 255 
logit 255 : -0.4784857 
logit mean 255 : -0.4269084 
logit RMSE 255 : 0.06895252 

boosting 255 : -0.6732916 
boosting mean 255 : -0.4991454 
boosting RMSE 255 : 0.1614037 

forest 255 : -0.454774 
forest mean 255 : -0.3804263 
forest RMSE 255 : 0.05287119 

nnet 255 : -0.3931036 
nnet mean 255 : -0.4309504 
nnet RMSE 255 : 0.1539032 


s: 256 
logit 256 : -0.3872316 
logit mean 256 : -0.4267534 
logit RMSE 256 : 0.06882234 

boosting 256 : -0.557287 
boosting mean 256 : -0.4993725 
boosting RMSE 256 : 0.1613878 

forest 256 : -0.3523826 
forest mean 256 : -0.3803167 
forest RMSE 256 : 0.05285168 

nnet 256 : -0.4592979 
nnet mean 256 : -0.4310611 
nnet RMSE 256 : 0.153647 


s: 257 
logit 257 : -0.5188931 
logit mean 257 : -0.427112 
logit RMSE 257 : 0.06908753 

boosting 257 : -0.6976863 
boosting mean 257 : -0.5001441 
boosting RMSE 257 : 0.1621404 

forest 257 : -0.4582523 
forest mean 257 : -0.3806200 
forest RMSE 257 : 0.05287377 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Warning in MatchLoopCfast(N = s1$N, xvars = Kx, All = s1$All, M = s1$M,  :
  Increasing memory because of ties.  I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.
Warning in MatchLoopCfast(N = s1$N, xvars = Kx, All = s1$All, M = s1$M,  :
  Increasing memory because of ties.  I would be faster with the ties=FALSE option.

nnet 257 : -0.2968878 
nnet mean 257 : -0.430539 
nnet RMSE 257 : 0.1534826 


s: 258 
logit 258 : -0.4083618 
logit mean 258 : -0.4270393 
logit RMSE 258 : 0.06895547 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 258 : -0.6406751 
boosting mean 258 : -0.5006888 
boosting RMSE 258 : 0.1625181 

forest 258 : -0.3791145 
forest mean 258 : -0.3806141 
forest RMSE 258 : 0.05278721 

nnet 258 : -0.4059525 
nnet mean 258 : -0.4304437 
nnet RMSE 258 : 0.1531853 


s: 259 
logit 259 : -0.3792849 
logit mean 259 : -0.4268549 
logit RMSE 259 : 0.06883426 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 259 : -0.427264 
boosting mean 259 : -0.5004053 
boosting RMSE 259 : 0.1622129 

forest 259 : -0.3259069 
forest mean 259 : -0.3804029 
forest RMSE 259 : 0.05288599 

nnet 259 : -0.3607726 
nnet mean 259 : -0.4301747 
nnet RMSE 259 : 0.1529087 


s: 260 
logit 260 : -0.5751437 
logit mean 260 : -0.4274253 
logit RMSE 260 : 0.06955511 

boosting 260 : -0.4870222 
boosting mean 260 : -0.5003539 
boosting RMSE 260 : 0.1619905 

forest 260 : -0.4846447 
forest mean 260 : -0.3808038 
forest RMSE 260 : 0.05304457 

nnet 260 : -0.2906630 
nnet mean 260 : -0.4296382 
nnet RMSE 260 : 0.1527650 


s: 261 
logit 261 : -0.3303877 
logit mean 261 : -0.4270535 
logit RMSE 261 : 0.06955533 

boosting 261 : -0.3693599 
boosting mean 261 : -0.499852 
boosting RMSE 261 : 0.1616910 

forest 261 : -0.2698917 
forest mean 261 : -0.3803789 
forest RMSE 261 : 0.05355189 

nnet 261 : -0.4265893 
nnet mean 261 : -0.4296265 
nnet RMSE 261 : 0.1524809 


s: 262 
logit 262 : -0.5140819 
logit mean 262 : -0.4273856 
logit RMSE 262 : 0.06977932 

boosting 262 : -0.4311702 
boosting mean 262 : -0.4995898 
boosting RMSE 262 : 0.1613937 

forest 262 : -0.3469001 
forest mean 262 : -0.3802511 
forest RMSE 262 : 0.05355017 

nnet 262 : -0.2116362 
nnet mean 262 : -0.4287945 
nnet RMSE 262 : 0.1526339 


s: 263 
logit 263 : -0.404167 
logit mean 263 : -0.4272973 
logit RMSE 263 : 0.069647 

boosting 263 : -0.3789165 
boosting mean 263 : -0.499131 
boosting RMSE 263 : 0.1610918 

forest 263 : -0.3947524 
forest mean 263 : -0.3803062 
forest RMSE 263 : 0.05344925 

nnet 263 : -0.7414123 
nnet mean 263 : -0.4299831 
nnet RMSE 263 : 0.1537912 


s: 264 
logit 264 : -0.4345695 
logit mean 264 : -0.4273249 
logit RMSE 264 : 0.06954753 

boosting 264 : -0.3599046 
boosting mean 264 : -0.4986036 
boosting RMSE 264 : 0.1608053 

forest 264 : -0.3899633 
forest mean 264 : -0.3803428 
forest RMSE 264 : 0.0533515 

nnet 264 : -0.5450219 
nnet mean 264 : -0.4304189 
nnet RMSE 264 : 0.1537589 


s: 265 
logit 265 : -0.4071702 
logit mean 265 : -0.4272488 
logit RMSE 265 : 0.06941758 

boosting 265 : -0.4622131 
boosting mean 265 : -0.4984663 
boosting RMSE 265 : 0.1605471 

forest 265 : -0.4083673 
forest mean 265 : -0.3804486 
forest RMSE 265 : 0.05325322 

nnet 265 : -0.2823572 
nnet mean 265 : -0.4298601 
nnet RMSE 265 : 0.1536386 


s: 266 
logit 266 : -0.464539 
logit mean 266 : -0.427389 
logit RMSE 266 : 0.06939988 

boosting 266 : -0.4826093 
boosting mean 266 : -0.4984067 
boosting RMSE 266 : 0.1603251 

forest 266 : -0.3921603 
forest mean 266 : -0.3804926 
forest RMSE 266 : 0.0531552 

nnet 266 : -0.5650934 
nnet mean 266 : -0.4303685 
nnet RMSE 266 : 0.1536833 


s: 267 
logit 267 : -0.42188 
logit mean 267 : -0.4273684 
logit RMSE 267 : 0.06928274 

boosting 267 : -0.4823602 
boosting mean 267 : -0.4983466 
boosting RMSE 267 : 0.1601039 

forest 267 : -0.3955476 
forest mean 267 : -0.380549 
forest RMSE 267 : 0.05305627 

nnet 267 : -0.4712463 
nnet mean 267 : -0.4305216 
nnet RMSE 267 : 0.1534571 


s: 268 
logit 268 : -0.3303344 
logit mean 268 : -0.4270063 
logit RMSE 268 : 0.06928417 

boosting 268 : -0.2525938 
boosting mean 268 : -0.4974296 
boosting RMSE 268 : 0.1600584 

forest 268 : -0.3148676 
forest mean 268 : -0.3803039 
forest RMSE 268 : 0.0532119 

nnet 268 : -0.516224 
nnet mean 268 : -0.4308414 
nnet RMSE 268 : 0.1533350 


s: 269 
logit 269 : -0.5417834 
logit mean 269 : -0.427433 
logit RMSE 269 : 0.06969348 

boosting 269 : -0.7634133 
boosting mean 269 : -0.4984184 
boosting RMSE 269 : 0.1612899 

forest 269 : -0.4589666 
forest mean 269 : -0.3805963 
forest RMSE 269 : 0.05323445 

nnet 269 : -0.6066347 
nnet mean 269 : -0.4314949 
nnet RMSE 269 : 0.1535674 


s: 270 
logit 270 : -0.3446375 
logit mean 270 : -0.4271264 
logit RMSE 270 : 0.06964585 

boosting 270 : -0.5241667 
boosting mean 270 : -0.4985137 
boosting RMSE 270 : 0.1611682 

forest 270 : -0.3748107 
forest mean 270 : -0.3805749 
forest RMSE 270 : 0.05315788 

nnet 270 : -0.7234979 
nnet mean 270 : -0.4325764 
nnet RMSE 270 : 0.1545419 


s: 271 
logit 271 : -0.4143735 
logit mean 271 : -0.4270793 
logit RMSE 271 : 0.06952271 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 271 : -0.5873461 
boosting mean 271 : -0.4988415 
boosting RMSE 271 : 0.1612726 

forest 271 : -0.4091505 
forest mean 271 : -0.3806803 
forest RMSE 271 : 0.05306263 

nnet 271 : -0.5148973 
nnet mean 271 : -0.4328802 
nnet RMSE 271 : 0.1544143 


s: 272 
logit 272 : -0.3509709 
logit mean 272 : -0.4267995 
logit RMSE 272 : 0.06945844 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 272 : -0.5104891 
boosting mean 272 : -0.4988844 
boosting RMSE 272 : 0.1611152 

forest 272 : -0.3585495 
forest mean 272 : -0.380599 
forest RMSE 272 : 0.05302459 

nnet 272 : -0.4445712 
nnet mean 272 : -0.4329232 
nnet RMSE 272 : 0.1541539 


s: 273 
logit 273 : -0.3853974 
logit mean 273 : -0.4266478 
logit RMSE 273 : 0.06933675 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 273 : -0.6069786 
boosting mean 273 : -0.4992803 
boosting RMSE 273 : 0.161307 

forest 273 : -0.4468363 
forest mean 273 : -0.3808416 
forest RMSE 273 : 0.05300324 

nnet 273 : -0.2804856 
nnet mean 273 : -0.4323648 
nnet RMSE 273 : 0.1540413 


s: 274 
logit 274 : -0.3046696 
logit mean 274 : -0.4262027 
logit RMSE 274 : 0.0694493 

boosting 274 : -0.2870480 
boosting mean 274 : -0.4985057 
boosting RMSE 274 : 0.1611569 

forest 274 : -0.3551101 
forest mean 274 : -0.3807477 
forest RMSE 274 : 0.05297589 

nnet 274 : -0.4759109 
nnet mean 274 : -0.4325237 
nnet RMSE 274 : 0.1538283 


s: 275 
logit 275 : -0.4184315 
logit mean 275 : -0.4261744 
logit RMSE 275 : 0.06933183 

boosting 275 : -0.5771516 
boosting mean 275 : -0.4987917 
boosting RMSE 275 : 0.1612179 

forest 275 : -0.3033687 
forest mean 275 : -0.3804663 
forest RMSE 275 : 0.05319958 

nnet 275 : -0.3835477 
nnet mean 275 : -0.4323456 
nnet RMSE 275 : 0.1535515 


s: 276 
logit 276 : -0.4502545 
logit mean 276 : -0.4262616 
logit RMSE 276 : 0.06927219 

boosting 276 : -0.4104186 
boosting mean 276 : -0.4984715 
boosting RMSE 276 : 0.1609268 

forest 276 : -0.354903 
forest mean 276 : -0.3803737 
forest RMSE 276 : 0.05317245 

nnet 276 : -0.3901074 
nnet mean 276 : -0.4321926 
nnet RMSE 276 : 0.1532743 


s: 277 
logit 277 : -0.3977364 
logit mean 277 : -0.4261587 
logit RMSE 277 : 0.06914717 

boosting 277 : -0.5545772 
boosting mean 277 : -0.4986741 
boosting RMSE 277 : 0.1609043 

forest 277 : -0.3271161 
forest mean 277 : -0.3801814 
forest RMSE 277 : 0.05325673 

nnet 277 : -0.3919356 
nnet mean 277 : -0.4320473 
nnet RMSE 277 : 0.1529981 


s: 278 
logit 278 : -0.4349511 
logit mean 278 : -0.4261903 
logit RMSE 278 : 0.06905452 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 278 : -0.7780311 
boosting mean 278 : -0.499679 
boosting RMSE 278 : 0.1622071 

forest 278 : -0.3506619 
forest mean 278 : -0.3800752 
forest RMSE 278 : 0.05324315 

nnet 278 : -0.2279464 
nnet mean 278 : -0.4313131 
nnet RMSE 278 : 0.1530709 


s: 279 
logit 279 : -0.3747277 
logit mean 279 : -0.4260058 
logit RMSE 279 : 0.06894726 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 279 : -0.3672134 
boosting mean 279 : -0.4992042 
boosting RMSE 279 : 0.1619280 

forest 279 : -0.3470337 
forest mean 279 : -0.3799568 
forest RMSE 279 : 0.05324216 

nnet 279 : -0.3694565 
nnet mean 279 : -0.4310914 
nnet RMSE 279 : 0.1528073 


s: 280 
logit 280 : -0.3912245 
logit mean 280 : -0.4258816 
logit RMSE 280 : 0.06882602 

boosting 280 : -0.336317 
boosting mean 280 : -0.4986224 
boosting RMSE 280 : 0.1616834 

forest 280 : -0.4633056 
forest mean 280 : -0.3802545 
forest RMSE 280 : 0.05328149 

nnet 280 : -0.3960148 
nnet mean 280 : -0.4309661 
nnet RMSE 280 : 0.1525344 


s: 281 
logit 281 : -0.4267746 
logit mean 281 : -0.4258848 
logit RMSE 281 : 0.06872201 

boosting 281 : -0.5562173 
boosting mean 281 : -0.4988274 
boosting RMSE 281 : 0.1616643 

forest 281 : -0.2997408 
forest mean 281 : -0.379968 
forest RMSE 281 : 0.05352182 

nnet 281 : -0.3540417 
nnet mean 281 : -0.4306923 
nnet RMSE 281 : 0.1522874 


s: 282 
logit 282 : -0.3983044 
logit mean 282 : -0.425787 
logit RMSE 282 : 0.06860013 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 282 : -0.4434221 
boosting mean 282 : -0.4986309 
boosting RMSE 282 : 0.1613981 

forest 282 : -0.3252296 
forest mean 282 : -0.3797739 
forest RMSE 282 : 0.05361206 

nnet 282 : -0.4075644 
nnet mean 282 : -0.4306103 
nnet RMSE 282 : 0.1520178 


s: 283 
logit 283 : -0.3619807 
logit mean 283 : -0.4255615 
logit RMSE 283 : 0.0685161 

boosting 283 : -0.2919755 
boosting mean 283 : -0.4979007 
boosting RMSE 283 : 0.1612406 

forest 283 : -0.3513701 
forest mean 283 : -0.3796735 
forest RMSE 283 : 0.05359527 

nnet 283 : -0.2557408 
nnet mean 283 : -0.4299924 
nnet RMSE 283 : 0.1519911 


s: 284 
logit 284 : -0.4381068 
logit mean 284 : -0.4256057 
logit RMSE 284 : 0.06843274 

boosting 284 : -0.5849463 
boosting mean 284 : -0.4982072 
boosting RMSE 284 : 0.1613302 

forest 284 : -0.3578293 
forest mean 284 : -0.3795966 
forest RMSE 284 : 0.05355931 

nnet 284 : -0.5408504 
nnet mean 284 : -0.4303828 
nnet RMSE 284 : 0.1519533 


s: 285 
logit 285 : -0.5558141 
logit mean 285 : -0.4260626 
logit RMSE 285 : 0.06893326 

boosting 285 : -0.5305536 
boosting mean 285 : -0.4983207 
boosting RMSE 285 : 0.1612325 

forest 285 : -0.3670502 
forest mean 285 : -0.3795526 
forest RMSE 285 : 0.05350088 

nnet 285 : -0.3236718 
nnet mean 285 : -0.4300083 
nnet RMSE 285 : 0.1517538 


s: 286 
logit 286 : -0.4353921 
logit mean 286 : -0.4260952 
logit RMSE 286 : 0.06884446 

boosting 286 : -0.4581448 
boosting mean 286 : -0.4981802 
boosting RMSE 286 : 0.1609871 

forest 286 : -0.2975872 
forest mean 286 : -0.379266 
forest RMSE 286 : 0.0537495 

nnet 286 : -0.4907696 
nnet mean 286 : -0.4302208 
nnet RMSE 286 : 0.1515833 


s: 287 
logit 287 : -0.4051706 
logit mean 287 : -0.4260223 
logit RMSE 287 : 0.0687251 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 287 : -0.4284158 
boosting mean 287 : -0.4979371 
boosting RMSE 287 : 0.1607151 

forest 287 : -0.3468529 
forest mean 287 : -0.379153 
forest RMSE 287 : 0.05374741 

nnet 287 : -0.406479 
nnet mean 287 : -0.4301381 
nnet RMSE 287 : 0.1513195 


s: 288 
logit 288 : -0.4594745 
logit mean 288 : -0.4261384 
logit RMSE 288 : 0.06869513 

boosting 288 : -0.5576981 
boosting mean 288 : -0.4981446 
boosting RMSE 288 : 0.1607047 

forest 288 : -0.3405535 
forest mean 288 : -0.379019 
forest RMSE 288 : 0.05376825 

nnet 288 : -0.5644376 
nnet mean 288 : -0.4306044 
nnet RMSE 288 : 0.1513670 


s: 289 
logit 289 : -0.4005722 
logit mean 289 : -0.42605 
logit RMSE 289 : 0.06857619 

boosting 289 : -0.478927 
boosting mean 289 : -0.4980781 
boosting RMSE 289 : 0.1604936 

forest 289 : -0.3160063 
forest mean 289 : -0.378801 
forest RMSE 289 : 0.05390206 

nnet 289 : -0.2752228 
nnet mean 289 : -0.4300667 
nnet RMSE 289 : 0.1512831 


s: 290 
logit 290 : -0.3559561 
logit mean 290 : -0.4258083 
logit RMSE 290 : 0.06850669 

boosting 290 : -0.3867938 
boosting mean 290 : -0.4976944 
boosting RMSE 290 : 0.1602185 

forest 290 : -0.3614296 
forest mean 290 : -0.3787411 
forest RMSE 290 : 0.05385669 

nnet 290 : -0.1559609 
nnet mean 290 : -0.4291215 
nnet RMSE 290 : 0.1517004 


s: 291 
logit 291 : -0.2957669 
logit mean 291 : -0.4253614 
logit RMSE 291 : 0.0686613 

boosting 291 : -0.7655663 
boosting mean 291 : -0.4986149 
boosting RMSE 291 : 0.1613723 

forest 291 : -0.3378028 
forest mean 291 : -0.3786004 
forest RMSE 291 : 0.05388757 

nnet 291 : -0.4954326 
nnet mean 291 : -0.4293494 
nnet RMSE 291 : 0.1515428 


s: 292 
logit 292 : -0.3702106 
logit mean 292 : -0.4251725 
logit RMSE 292 : 0.06856579 

boosting 292 : -0.3283225 
boosting mean 292 : -0.4980317 
boosting RMSE 292 : 0.1611503 

forest 292 : -0.4042042 
forest mean 292 : -0.3786881 
forest RMSE 292 : 0.05379578 

nnet 292 : -0.1783581 
nnet mean 292 : -0.4284899 
nnet RMSE 292 : 0.1518381 


s: 293 
logit 293 : -0.4266589 
logit mean 293 : -0.4251776 
logit RMSE 293 : 0.0684664 

boosting 293 : -0.4580863 
boosting mean 293 : -0.4978954 
boosting RMSE 293 : 0.1609109 

forest 293 : -0.3831237 
forest mean 293 : -0.3787032 
forest RMSE 293 : 0.05371295 

nnet 293 : -0.4140041 
nnet mean 293 : -0.4284404 
nnet RMSE 293 : 0.151581 


s: 294 
logit 294 : -0.3552379 
logit mean 294 : -0.4249397 
logit RMSE 294 : 0.0683997 

boosting 294 : -0.4211642 
boosting mean 294 : -0.4976344 
boosting RMSE 294 : 0.1606417 

forest 294 : -0.2830503 
forest mean 294 : -0.3783779 
forest RMSE 294 : 0.05405357 

nnet 294 : -0.393988 
nnet mean 294 : -0.4283232 
nnet RMSE 294 : 0.1513234 


s: 295 
logit 295 : -0.3620937 
logit mean 295 : -0.4247267 
logit RMSE 295 : 0.06831932 

boosting 295 : -0.6200226 
boosting mean 295 : -0.4980493 
boosting RMSE 295 : 0.1608800 

forest 295 : -0.3920818 
forest mean 295 : -0.3784243 
forest RMSE 295 : 0.05396385 

nnet 295 : -0.4112325 
nnet mean 295 : -0.4282653 
nnet RMSE 295 : 0.1510681 


s: 296 
logit 296 : -0.4113139 
logit mean 296 : -0.4246814 
logit RMSE 296 : 0.068207 

boosting 296 : -0.5847116 
boosting mean 296 : -0.4983421 
boosting RMSE 296 : 0.1609665 

forest 296 : -0.3608148 
forest mean 296 : -0.3783648 
forest RMSE 296 : 0.05392074 

nnet 296 : -0.3737216 
nnet mean 296 : -0.428081 
nnet RMSE 296 : 0.1508205 


s: 297 
logit 297 : -0.5535916 
logit mean 297 : -0.4251154 
logit RMSE 297 : 0.06867284 

boosting 297 : -0.6135094 
boosting mean 297 : -0.4987298 
boosting RMSE 297 : 0.1611721 

forest 297 : -0.4696788 
forest mean 297 : -0.3786723 
forest RMSE 297 : 0.05398151 

nnet 297 : -0.5511773 
nnet mean 297 : -0.4284955 
nnet RMSE 297 : 0.1508217 


s: 298 
logit 298 : -0.4985053 
logit mean 298 : -0.4253617 
logit RMSE 298 : 0.06879458 

boosting 298 : -0.6378156 
boosting mean 298 : -0.4991966 
boosting RMSE 298 : 0.1614902 

forest 298 : -0.4321183 
forest mean 298 : -0.3788516 
forest RMSE 298 : 0.05392297 

nnet 298 : -0.4828478 
nnet mean 298 : -0.4286779 
nnet RMSE 298 : 0.1506449 


s: 299 
logit 299 : -0.448935 
logit mean 299 : -0.4254405 
logit RMSE 299 : 0.06873773 

boosting 299 : -0.3532245 
boosting mean 299 : -0.4987084 
boosting RMSE 299 : 0.1612426 

forest 299 : -0.4023134 
forest mean 299 : -0.3789301 
forest RMSE 299 : 0.05383289 

nnet 299 : -0.2716309 
nnet mean 299 : -0.4281526 
nnet RMSE 299 : 0.1505759 


s: 300 
logit 300 : -0.5681815 
logit mean 300 : -0.4259163 
logit RMSE 300 : 0.06930663 

boosting 300 : -0.5592267 
boosting mean 300 : -0.4989101 
boosting RMSE 300 : 0.1612359 

forest 300 : -0.4009666 
forest mean 300 : -0.3790035 
forest RMSE 300 : 0.05374312 

nnet 300 : -0.4281344 
nnet mean 300 : -0.4281526 
nnet RMSE 300 : 0.1503335 


s: 301 
logit 301 : -0.3402341 
logit mean 301 : -0.4256317 
logit RMSE 301 : 0.06927711 

boosting 301 : -0.495997 
boosting mean 301 : -0.4989004 
boosting RMSE 301 : 0.1610629 

forest 301 : -0.3146997 
forest mean 301 : -0.3787899 
forest RMSE 301 : 0.05387858 

nnet 301 : -0.482805 
nnet mean 301 : -0.4283342 
nnet RMSE 301 : 0.1501594 


s: 302 
logit 302 : -0.3078680 
logit mean 302 : -0.4252417 
logit RMSE 302 : 0.06936522 

boosting 302 : -0.4583198 
boosting mean 302 : -0.498766 
boosting RMSE 302 : 0.1608311 

forest 302 : -0.4427385 
forest mean 302 : -0.3790017 
forest RMSE 302 : 0.05384549 

nnet 302 : -0.3558419 
nnet mean 302 : -0.4280941 
nnet RMSE 302 : 0.1499321 


s: 303 
logit 303 : -0.4468876 
logit mean 303 : -0.4253132 
logit RMSE 303 : 0.06930302 

boosting 303 : -0.5564855 
boosting mean 303 : -0.4989565 
boosting RMSE 303 : 0.1608169 

forest 303 : -0.3342444 
forest mean 303 : -0.3788539 
forest RMSE 303 : 0.05388913 

nnet 303 : -0.5977513 
nnet mean 303 : -0.428654 
nnet RMSE 303 : 0.150115 


s: 304 
logit 304 : -0.4465514 
logit mean 304 : -0.425383 
logit RMSE 304 : 0.06924044 

boosting 304 : -0.5594392 
boosting mean 304 : -0.4991555 
boosting RMSE 304 : 0.1608124 

forest 304 : -0.3592829 
forest mean 304 : -0.3787896 
forest RMSE 304 : 0.05385108 

nnet 304 : -0.3138616 
nnet mean 304 : -0.4282764 
nnet RMSE 304 : 0.1499493 


s: 305 
logit 305 : -0.3479226 
logit mean 305 : -0.4251290 
logit RMSE 305 : 0.06919112 

boosting 305 : -0.3927769 
boosting mean 305 : -0.4988067 
boosting RMSE 305 : 0.1605491 

forest 305 : -0.2520343 
forest mean 305 : -0.378374 
forest RMSE 305 : 0.05442623 

nnet 305 : -0.3579381 
nnet mean 305 : -0.4280458 
nnet RMSE 305 : 0.1497226 


s: 306 
logit 306 : -0.5365964 
logit mean 306 : -0.4254933 
logit RMSE 306 : 0.06951793 

boosting 306 : -0.5273181 
boosting mean 306 : -0.4988999 
boosting RMSE 306 : 0.1604517 

forest 306 : -0.3807572 
forest mean 306 : -0.3783818 
forest RMSE 306 : 0.05434835 

nnet 306 : -0.3777313 
nnet mean 306 : -0.4278814 
nnet RMSE 306 : 0.1494832 


s: 307 
logit 307 : -0.5036566 
logit mean 307 : -0.4257479 
logit RMSE 307 : 0.0696563 

boosting 307 : -0.5758749 
boosting mean 307 : -0.4991506 
boosting RMSE 307 : 0.1605043 

forest 307 : -0.425685 
forest mean 307 : -0.3785358 
forest RMSE 307 : 0.05427957 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Warning in MatchLoopCfast(N = s1$N, xvars = Kx, All = s1$All, M = s1$M,  :
  Increasing memory because of ties.  I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.
Warning in MatchLoopCfast(N = s1$N, xvars = Kx, All = s1$All, M = s1$M,  :
  Increasing memory because of ties.  I would be faster with the ties=FALSE option.

nnet 307 : -0.1663701 
nnet mean 307 : -0.4270296 
nnet RMSE 307 : 0.1498341 


s: 308 
logit 308 : -0.4251924 
logit mean 308 : -0.4257461 
logit RMSE 308 : 0.06955794 

boosting 308 : -0.6246348 
boosting mean 308 : -0.499558 
boosting RMSE 308 : 0.1607540 

forest 308 : -0.3741788 
forest mean 308 : -0.3785217 
forest RMSE 308 : 0.05421135 

nnet 308 : -0.4592532 
nnet mean 308 : -0.4271342 
nnet RMSE 308 : 0.1496287 


s: 309 
logit 309 : -0.4523374 
logit mean 309 : -0.4258322 
logit RMSE 309 : 0.06950909 

boosting 309 : -0.5999366 
boosting mean 309 : -0.4998829 
boosting RMSE 309 : 0.1608962 

forest 309 : -0.4370359 
forest mean 309 : -0.3787111 
forest RMSE 309 : 0.05416455 

nnet 309 : -0.4410741 
nnet mean 309 : -0.4271793 
nnet RMSE 309 : 0.1494047 


s: 310 
logit 310 : -0.4987025 
logit mean 310 : -0.4260672 
logit RMSE 310 : 0.06962294 

boosting 310 : -0.6207505 
boosting mean 310 : -0.5002728 
boosting RMSE 310 : 0.1611250 

forest 310 : -0.4410913 
forest mean 310 : -0.3789123 
forest RMSE 310 : 0.05412745 

nnet 310 : -0.5999584 
nnet mean 310 : -0.4277366 
nnet RMSE 310 : 0.1495952 


s: 311 
logit 311 : -0.3700596 
logit mean 311 : -0.4258872 
logit RMSE 311 : 0.06953165 

boosting 311 : -0.5373194 
boosting mean 311 : -0.5003919 
boosting RMSE 311 : 0.1610541 

forest 311 : -0.3766571 
forest mean 311 : -0.3789050 
forest RMSE 311 : 0.05405657 

nnet 311 : -0.3057696 
nnet mean 311 : -0.4273445 
nnet RMSE 311 : 0.1494501 


s: 312 
logit 312 : -0.4592072 
logit mean 312 : -0.4259939 
logit RMSE 312 : 0.06950101 

boosting 312 : -0.7373784 
boosting mean 312 : -0.5011515 
boosting RMSE 312 : 0.1619262 

forest 312 : -0.4299365 
forest mean 312 : -0.3790686 
forest RMSE 312 : 0.05399648 

nnet 312 : -0.6704175 
nnet mean 312 : -0.4281235 
nnet RMSE 312 : 0.1499937 


s: 313 
logit 313 : -0.4552001 
logit mean 313 : -0.4260873 
logit RMSE 313 : 0.06946001 

boosting 313 : -0.5146997 
boosting mean 313 : -0.5011948 
boosting RMSE 313 : 0.1617973 

forest 313 : -0.3534514 
forest mean 313 : -0.3789868 
forest RMSE 313 : 0.05397432 

nnet 313 : -0.7398564 
nnet mean 313 : -0.4291195 
nnet RMSE 313 : 0.1509810 


s: 314 
logit 314 : -0.4005057 
logit mean 314 : -0.4260058 
logit RMSE 314 : 0.06934932 

boosting 314 : -0.5528583 
boosting mean 314 : -0.5013593 
boosting RMSE 314 : 0.1617696 

forest 314 : -0.3568712 
forest mean 314 : -0.3789163 
forest RMSE 314 : 0.05394324 

nnet 314 : -0.3867293 
nnet mean 314 : -0.4289845 
nnet RMSE 314 : 0.1507422 


s: 315 
logit 315 : -0.5417825 
logit mean 315 : -0.4263733 
logit RMSE 315 : 0.06969847 

boosting 315 : -0.711441 
boosting mean 315 : -0.5020262 
boosting RMSE 315 : 0.1624631 

forest 315 : -0.462605 
forest mean 315 : -0.379182 
forest RMSE 315 : 0.05397294 

nnet 315 : -0.4592344 
nnet mean 315 : -0.4290805 
nnet RMSE 315 : 0.1505397 


s: 316 
logit 316 : -0.3908299 
logit mean 316 : -0.4262609 
logit RMSE 316 : 0.06959002 

boosting 316 : -0.3784591 
boosting mean 316 : -0.5016352 
boosting RMSE 316 : 0.1622103 

forest 316 : -0.3835727 
forest mean 316 : -0.3791959 
forest RMSE 316 : 0.05389539 

nnet 316 : -0.2756723 
nnet mean 316 : -0.4285951 
nnet RMSE 316 : 0.150464 


s: 317 
logit 317 : -0.3679236 
logit mean 317 : -0.4260768 
logit RMSE 317 : 0.06950352 

boosting 317 : -0.4661696 
boosting mean 317 : -0.5015233 
boosting RMSE 317 : 0.1619969 

forest 317 : -0.3802038 
forest mean 317 : -0.3791991 
forest RMSE 317 : 0.0538218 

nnet 317 : -0.2544487 
nnet mean 317 : -0.4280457 
nnet RMSE 317 : 0.1504488 


s: 318 
logit 318 : -0.3393296 
logit mean 318 : -0.425804 
logit RMSE 318 : 0.0694775 

boosting 318 : -0.4072796 
boosting mean 318 : -0.5012269 
boosting RMSE 318 : 0.1617425 

forest 318 : -0.3648978 
forest mean 318 : -0.3791541 
forest RMSE 318 : 0.05377315 

nnet 318 : -0.4496914 
nnet mean 318 : -0.4281138 
nnet RMSE 318 : 0.1502379 


s: 319 
logit 319 : -0.4340074 
logit mean 319 : -0.4258298 
logit RMSE 319 : 0.06939464 

boosting 319 : -0.537166 
boosting mean 319 : -0.5013396 
boosting RMSE 319 : 0.1616713 

forest 319 : -0.3629182 
forest mean 319 : -0.3791032 
forest RMSE 319 : 0.05372893 

nnet 319 : -0.6334348 
nnet mean 319 : -0.4287574 
nnet RMSE 319 : 0.1505705 


s: 320 
logit 320 : -0.43907 
logit mean 320 : -0.4258711 
logit RMSE 320 : 0.06932055 

boosting 320 : -0.6229584 
boosting mean 320 : -0.5017197 
boosting RMSE 320 : 0.1618990 

forest 320 : -0.4114127 
forest mean 320 : -0.3792042 
forest RMSE 320 : 0.0536487 

nnet 320 : -0.7295224 
nnet mean 320 : -0.4296973 
nnet RMSE 320 : 0.1514594 


s: 321 
logit 321 : -0.381484 
logit mean 321 : -0.4257328 
logit RMSE 321 : 0.0692202 

boosting 321 : -0.4429311 
boosting mean 321 : -0.5015365 
boosting RMSE 321 : 0.1616644 

forest 321 : -0.3159467 
forest mean 321 : -0.3790071 
forest RMSE 321 : 0.05377013 

nnet 321 : -0.5883327 
nnet mean 321 : -0.4301915 
nnet RMSE 321 : 0.1515882 


s: 322 
logit 322 : -0.4241015 
logit mean 322 : -0.4257278 
logit RMSE 322 : 0.06912568 

boosting 322 : -0.4840364 
boosting mean 322 : -0.5014822 
boosting RMSE 322 : 0.1614811 

forest 322 : -0.4502869 
forest mean 322 : -0.3792285 
forest RMSE 322 : 0.05375966 

nnet 322 : -0.4649001 
nnet mean 322 : -0.4302993 
nnet RMSE 322 : 0.1513959 


s: 323 
logit 323 : -0.4190514 
logit mean 323 : -0.4257071 
logit RMSE 323 : 0.06902673 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 323 : -0.4929909 
boosting mean 323 : -0.5014559 
boosting RMSE 323 : 0.1613139 

forest 323 : -0.5035509 
forest mean 323 : -0.3796134 
forest RMSE 323 : 0.05398473 

nnet 323 : -0.5224905 
nnet mean 323 : -0.4305847 
nnet RMSE 323 : 0.1513149 


s: 324 
logit 324 : -0.5173068 
logit mean 324 : -0.4259898 
logit RMSE 324 : 0.06922757 

boosting 324 : -0.5326758 
boosting mean 324 : -0.5015522 
boosting RMSE 324 : 0.1612333 

forest 324 : -0.3945496 
forest mean 324 : -0.3796595 
forest RMSE 324 : 0.0539022 

nnet 324 : -0.6902882 
nnet mean 324 : -0.4313863 
nnet RMSE 324 : 0.1519395 


s: 325 
logit 325 : -0.4719903 
logit mean 325 : -0.4261314 
logit RMSE 325 : 0.06923624 

boosting 325 : -0.5855721 
boosting mean 325 : -0.5018108 
boosting RMSE 325 : 0.1613138 

forest 325 : -0.3304551 
forest mean 325 : -0.3795081 
forest RMSE 325 : 0.05395729 

nnet 325 : -0.496479 
nnet mean 325 : -0.4315865 
nnet RMSE 325 : 0.1517999 


s: 326 
logit 326 : -0.372527 
logit mean 326 : -0.4259669 
logit RMSE 326 : 0.06914671 

boosting 326 : -0.5161905 
boosting mean 326 : -0.5018549 
boosting RMSE 326 : 0.1611947 

forest 326 : -0.3362983 
forest mean 326 : -0.3793755 
forest RMSE 326 : 0.05398987 

nnet 326 : -0.01811896 
nnet mean 326 : -0.4303182 
nnet RMSE 326 : 0.1530355 


s: 327 
logit 327 : -0.451169 
logit mean 327 : -0.426044 
logit RMSE 327 : 0.06909886 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 327 : -0.5563546 
boosting mean 327 : -0.5020215 
boosting RMSE 327 : 0.1611802 

forest 327 : -0.3582795 
forest mean 327 : -0.379311 
forest RMSE 327 : 0.0539566 

nnet 327 : -0.3899112 
nnet mean 327 : -0.4301947 
nnet RMSE 327 : 0.1528024 


s: 328 
logit 328 : -0.4634236 
logit mean 328 : -0.426158 
logit RMSE 328 : 0.06908227 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 328 : -0.6093326 
boosting mean 328 : -0.5023487 
boosting RMSE 328 : 0.1613488 

forest 328 : -0.5124757 
forest mean 328 : -0.379717 
forest RMSE 328 : 0.05423106 

nnet 328 : -0.3869489 
nnet mean 328 : -0.4300628 
nnet RMSE 328 : 0.1525710 


s: 329 
logit 329 : -0.4150692 
logit mean 329 : -0.4261243 
logit RMSE 329 : 0.0689822 

boosting 329 : -0.4172381 
boosting mean 329 : -0.50209 
boosting RMSE 329 : 0.1611062 

forest 329 : -0.3837172 
forest mean 329 : -0.3797292 
forest RMSE 329 : 0.05415602 

nnet 329 : -0.3878837 
nnet mean 329 : -0.4299346 
nnet RMSE 329 : 0.1523404 


s: 330 
logit 330 : -0.4531688 
logit mean 330 : -0.4262062 
logit RMSE 330 : 0.06893976 

boosting 330 : -0.4082369 
boosting mean 330 : -0.5018056 
boosting RMSE 330 : 0.1608626 

forest 330 : -0.3672937 
forest mean 330 : -0.3796915 
forest RMSE 330 : 0.05410387 

nnet 330 : -0.5570956 
nnet mean 330 : -0.4303200 
nnet RMSE 330 : 0.1523550 


s: 331 
logit 331 : -0.5560473 
logit mean 331 : -0.4265985 
logit RMSE 331 : 0.06936786 

boosting 331 : -0.7652655 
boosting mean 331 : -0.5026016 
boosting RMSE 331 : 0.1618693 

forest 331 : -0.3836512 
forest mean 331 : -0.3797034 
forest RMSE 331 : 0.05402956 

nnet 331 : -0.5694408 
nnet mean 331 : -0.4307403 
nnet RMSE 331 : 0.1524095 


s: 332 
logit 332 : -0.4094528 
logit mean 332 : -0.4265468 
logit RMSE 332 : 0.06926525 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 332 : -0.4631423 
boosting mean 332 : -0.5024827 
boosting RMSE 332 : 0.1616625 

forest 332 : -0.3301211 
forest mean 332 : -0.3795541 
forest RMSE 332 : 0.05408427 

nnet 332 : -0.2886365 
nnet mean 332 : -0.4303122 
nnet RMSE 332 : 0.1523025 


s: 333 
logit 333 : -0.4911742 
logit mean 333 : -0.4267409 
logit RMSE 333 : 0.0693414 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 333 : -0.5064991 
boosting mean 333 : -0.5024948 
boosting RMSE 333 : 0.1615250 

forest 333 : -0.4955031 
forest mean 333 : -0.3799023 
forest RMSE 333 : 0.054256 

nnet 333 : -0.5072183 
nnet mean 333 : -0.4305432 
nnet RMSE 333 : 0.1521871 


s: 334 
logit 334 : -0.4323501 
logit mean 334 : -0.4267577 
logit RMSE 334 : 0.06926015 

boosting 334 : -0.4769942 
boosting mean 334 : -0.5024184 
boosting RMSE 334 : 0.1613381 

forest 334 : -0.338687 
forest mean 334 : -0.3797789 
forest RMSE 334 : 0.0542785 

nnet 334 : -0.3517542 
nnet mean 334 : -0.4303073 
nnet RMSE 334 : 0.1519821 


s: 335 
logit 335 : -0.4673832 
logit mean 335 : -0.426879 
logit RMSE 335 : 0.06925462 

boosting 335 : -0.5300135 
boosting mean 335 : -0.5025008 
boosting RMSE 335 : 0.1612536 

forest 335 : -0.3935928 
forest mean 335 : -0.3798201 
forest RMSE 335 : 0.05419856 

nnet 335 : -0.4581035 
nnet mean 335 : -0.4303903 
nnet RMSE 335 : 0.1517882 


s: 336 
logit 336 : -0.4028135 
logit mean 336 : -0.4268074 
logit RMSE 336 : 0.06915166 

boosting 336 : -0.5540043 
boosting mean 336 : -0.5026541 
boosting RMSE 336 : 0.1612325 

forest 336 : -0.4627145 
forest mean 336 : -0.3800668 
forest RMSE 336 : 0.05422589 

nnet 336 : -0.2558960 
nnet mean 336 : -0.4298709 
nnet RMSE 336 : 0.1517660 


s: 337 
logit 337 : -0.3063825 
logit mean 337 : -0.42645 
logit RMSE 337 : 0.06923705 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 337 : -0.4827663 
boosting mean 337 : -0.5025951 
boosting RMSE 337 : 0.1610562 

forest 337 : -0.3837532 
forest mean 337 : -0.3800778 
forest RMSE 337 : 0.05415261 

nnet 337 : -0.4733329 
nnet mean 337 : -0.4299999 
nnet RMSE 337 : 0.1515933 


s: 338 
logit 338 : -0.4645437 
logit mean 338 : -0.4265627 
logit RMSE 338 : 0.06922363 

boosting 338 : -0.5421253 
boosting mean 338 : -0.502712 
boosting RMSE 338 : 0.1610035 

forest 338 : -0.4498182 
forest mean 338 : -0.3802841 
forest RMSE 338 : 0.0541403 

nnet 338 : -0.5138073 
nnet mean 338 : -0.4302479 
nnet RMSE 338 : 0.1514954 


s: 339 
logit 339 : -0.4454913 
logit mean 339 : -0.4266186 
logit RMSE 339 : 0.0691656 

boosting 339 : -0.455814 
boosting mean 339 : -0.5025737 
boosting RMSE 339 : 0.1607944 

forest 339 : -0.3878464 
forest mean 339 : -0.3803064 
forest RMSE 339 : 0.05406441 

nnet 339 : -0.5392461 
nnet mean 339 : -0.4305694 
nnet RMSE 339 : 0.1514607 


s: 340 
logit 340 : -0.4496267 
logit mean 340 : -0.4266862 
logit RMSE 340 : 0.06911623 

boosting 340 : -0.2762979 
boosting mean 340 : -0.5019081 
boosting RMSE 340 : 0.1606979 

forest 340 : -0.3593236 
forest mean 340 : -0.3802447 
forest RMSE 340 : 0.0540299 

nnet 340 : -0.260138 
nnet mean 340 : -0.4300681 
nnet RMSE 340 : 0.1514279 


s: 341 
logit 341 : -0.4535225 
logit mean 341 : -0.4267649 
logit RMSE 341 : 0.06907565 

boosting 341 : -0.2782389 
boosting mean 341 : -0.5012522 
boosting RMSE 341 : 0.1605975 

forest 341 : -0.3206867 
forest mean 341 : -0.3800701 
forest RMSE 341 : 0.05412132 

nnet 341 : -0.3312778 
nnet mean 341 : -0.4297784 
nnet RMSE 341 : 0.1512515 


s: 342 
logit 342 : -0.432847 
logit mean 342 : -0.4267827 
logit RMSE 342 : 0.06899745 

boosting 342 : -0.6850097 
boosting mean 342 : -0.5017895 
boosting RMSE 342 : 0.1611014 

forest 342 : -0.3951848 
forest mean 342 : -0.3801142 
forest RMSE 342 : 0.05404276 

nnet 342 : -0.3215485 
nnet mean 342 : -0.4294619 
nnet RMSE 342 : 0.1510897 


s: 343 
logit 343 : -0.4788504 
logit mean 343 : -0.4269345 
logit RMSE 343 : 0.06902822 

boosting 343 : -0.4448064 
boosting mean 343 : -0.5016234 
boosting RMSE 343 : 0.1608846 

forest 343 : -0.2811404 
forest mean 343 : -0.3798257 
forest RMSE 343 : 0.05434421 

nnet 343 : -0.7901525 
nnet mean 343 : -0.4305135 
nnet RMSE 343 : 0.152333 


s: 344 
logit 344 : -0.3731078 
logit mean 344 : -0.426778 
logit RMSE 344 : 0.06894306 

boosting 344 : -0.6146905 
boosting mean 344 : -0.5019521 
boosting RMSE 344 : 0.1610671 

forest 344 : -0.4142087 
forest mean 344 : -0.3799256 
forest RMSE 344 : 0.05427057 

nnet 344 : -0.2192395 
nnet mean 344 : -0.4298994 
nnet RMSE 344 : 0.1524233 


s: 345 
logit 345 : -0.276717 
logit mean 345 : -0.4263431 
logit RMSE 345 : 0.0691623 

boosting 345 : -0.4456237 
boosting mean 345 : -0.5017888 
boosting RMSE 345 : 0.1608522 

forest 345 : -0.2901030 
forest mean 345 : -0.3796653 
forest RMSE 345 : 0.0545139 

nnet 345 : -0.4765105 
nnet mean 345 : -0.4300345 
nnet RMSE 345 : 0.152258 


s: 346 
logit 346 : -0.4470824 
logit mean 346 : -0.426403 
logit RMSE 346 : 0.06910865 

boosting 346 : -0.5277915 
boosting mean 346 : -0.501864 
boosting RMSE 346 : 0.1607665 

forest 346 : -0.4284433 
forest mean 346 : -0.3798063 
forest RMSE 346 : 0.05445654 

nnet 346 : -0.3575760 
nnet mean 346 : -0.429825 
nnet RMSE 346 : 0.1520549 


s: 347 
logit 347 : -0.4704719 
logit mean 347 : -0.42653 
logit RMSE 347 : 0.06911261 

boosting 347 : -0.476274 
boosting mean 347 : -0.5017902 
boosting RMSE 347 : 0.1605869 

forest 347 : -0.4197112 
forest mean 347 : -0.3799213 
forest RMSE 347 : 0.05438831 

nnet 347 : -0.4774184 
nnet mean 347 : -0.4299622 
nnet RMSE 347 : 0.1518925 


s: 348 
logit 348 : -0.4008878 
logit mean 348 : -0.4264563 
logit RMSE 348 : 0.06901326 

boosting 348 : -0.423245 
boosting mean 348 : -0.5015645 
boosting RMSE 348 : 0.1603608 

forest 348 : -0.3575589 
forest mean 348 : -0.379857 
forest RMSE 348 : 0.05435774 

nnet 348 : -0.4951995 
nnet mean 348 : -0.4301497 
nnet RMSE 348 : 0.1517600 


s: 349 
logit 349 : -0.3638905 
logit mean 349 : -0.4262771 
logit RMSE 349 : 0.06894142 

boosting 349 : -0.4355432 
boosting mean 349 : -0.5013753 
boosting RMSE 349 : 0.1601422 

forest 349 : -0.35636 
forest mean 349 : -0.3797897 
forest RMSE 349 : 0.05433005 

nnet 349 : -0.3469622 
nnet mean 349 : -0.4299113 
nnet RMSE 349 : 0.1515690 


s: 350 
logit 350 : -0.4417259 
logit mean 350 : -0.4263212 
logit RMSE 350 : 0.06887898 

boosting 350 : -0.4139667 
boosting mean 350 : -0.5011256 
boosting RMSE 350 : 0.159915 

forest 350 : -0.4526452 
forest mean 350 : -0.3799978 
forest RMSE 350 : 0.05432531 

nnet 350 : -0.4452966 
nnet mean 350 : -0.4299553 
nnet RMSE 350 : 0.1513717 


s: 351 
logit 351 : -0.4278105 
logit mean 351 : -0.4263254 
logit RMSE 351 : 0.0687968 

boosting 351 : -0.5041696 
boosting mean 351 : -0.5011343 
boosting RMSE 351 : 0.1597838 

forest 351 : -0.3453968 
forest mean 351 : -0.3798993 
forest RMSE 351 : 0.0543261 

nnet 351 : -0.3835099 
nnet mean 351 : -0.4298229 
nnet RMSE 351 : 0.1511584 


s: 352 
logit 352 : -0.3262761 
logit mean 352 : -0.4260412 
logit RMSE 352 : 0.0688113 

boosting 352 : -0.4197473 
boosting mean 352 : -0.5009031 
boosting RMSE 352 : 0.1595601 

forest 352 : -0.4356115 
forest mean 352 : -0.3800575 
forest RMSE 352 : 0.05428208 

nnet 352 : -0.2917584 
nnet mean 352 : -0.4294307 
nnet RMSE 352 : 0.1510538 


s: 353 
logit 353 : -0.4545996 
logit mean 353 : -0.4261221 
logit RMSE 353 : 0.06877519 

boosting 353 : -0.5153104 
boosting mean 353 : -0.5009439 
boosting RMSE 353 : 0.1594521 

forest 353 : -0.3600294 
forest mean 353 : -0.3800008 
forest RMSE 353 : 0.05424687 

nnet 353 : -0.3418632 
nnet mean 353 : -0.4291826 
nnet RMSE 353 : 0.1508714 


s: 354 
logit 354 : -0.4008089 
logit mean 354 : -0.4260506 
logit RMSE 354 : 0.068678 

boosting 354 : -0.6851671 
boosting mean 354 : -0.5014643 
boosting RMSE 354 : 0.1599465 

forest 354 : -0.3648217 
forest mean 354 : -0.3799579 
forest RMSE 354 : 0.05420245 

nnet 354 : -0.503242 
nnet mean 354 : -0.4293918 
nnet RMSE 354 : 0.1507581 


s: 355 
logit 355 : -0.4278135 
logit mean 355 : -0.4260556 
logit RMSE 355 : 0.06859708 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 355 : -0.3956638 
boosting mean 355 : -0.5011662 
boosting RMSE 355 : 0.1597212 

forest 355 : -0.3853708 
forest mean 355 : -0.3799732 
forest RMSE 355 : 0.05413162 

nnet 355 : -0.6079612 
nnet mean 355 : -0.4298949 
nnet RMSE 355 : 0.1509496 


s: 356 
logit 356 : -0.321119 
logit mean 356 : -0.4257608 
logit RMSE 356 : 0.06862813 

boosting 356 : -0.3929291 
boosting mean 356 : -0.5008622 
boosting RMSE 356 : 0.1594972 

forest 356 : -0.4080103 
forest mean 356 : -0.3800519 
forest RMSE 356 : 0.05405721 

nnet 356 : -0.377629 
nnet mean 356 : -0.4297480 
nnet RMSE 356 : 0.1507421 


s: 357 
logit 357 : -0.4354923 
logit mean 357 : -0.4257881 
logit RMSE 357 : 0.06855768 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 357 : -0.5737699 
boosting mean 357 : -0.5010664 
boosting RMSE 357 : 0.1595389 

forest 357 : -0.3621706 
forest mean 357 : -0.3800018 
forest RMSE 357 : 0.05401856 

nnet 357 : -0.3559588 
nnet mean 357 : -0.4295414 
nnet RMSE 357 : 0.1505489 


s: 358 
logit 358 : -0.4780642 
logit mean 358 : -0.4259341 
logit RMSE 358 : 0.06858607 

boosting 358 : -0.5653308 
boosting mean 358 : -0.5012459 
boosting RMSE 358 : 0.1595554 

forest 358 : -0.4276755 
forest mean 358 : -0.380135 
forest RMSE 358 : 0.05396289 

nnet 358 : -0.2216120 
nnet mean 358 : -0.4289605 
nnet RMSE 358 : 0.1506339 


s: 359 
logit 359 : -0.555677 
logit mean 359 : -0.4262955 
logit RMSE 359 : 0.06898155 

boosting 359 : -0.4573428 
boosting mean 359 : -0.5011237 
boosting RMSE 359 : 0.1593618 

forest 359 : -0.3506664 
forest mean 359 : -0.3800529 
forest RMSE 359 : 0.05395055 

nnet 359 : -0.5679229 
nnet mean 359 : -0.4293476 
nnet RMSE 359 : 0.1506848 


s: 360 
logit 360 : -0.4385271 
logit mean 360 : -0.4263295 
logit RMSE 360 : 0.0689156 

boosting 360 : -0.4612173 
boosting mean 360 : -0.5010128 
boosting RMSE 360 : 0.159173 

forest 360 : -0.4774184 
forest mean 360 : -0.3803234 
forest RMSE 360 : 0.05402986 

nnet 360 : -0.4389546 
nnet mean 360 : -0.4293743 
nnet RMSE 360 : 0.1504893 


s: 361 
logit 361 : -0.4394138 
logit mean 361 : -0.4263657 
logit RMSE 361 : 0.06885133 

boosting 361 : -0.6337182 
boosting mean 361 : -0.5013804 
boosting RMSE 361 : 0.1594276 

forest 361 : -0.4096976 
forest mean 361 : -0.3804047 
forest RMSE 361 : 0.05395738 

nnet 361 : -0.4494784 
nnet mean 361 : -0.42943 
nnet RMSE 361 : 0.1503033 


s: 362 
logit 362 : -0.445045 
logit mean 362 : -0.4264173 
logit RMSE 362 : 0.06879692 

boosting 362 : -0.4773056 
boosting mean 362 : -0.5013139 
boosting RMSE 362 : 0.1592591 

forest 362 : -0.4592013 
forest mean 362 : -0.3806224 
forest RMSE 362 : 0.05397257 

nnet 362 : -0.472598 
nnet mean 362 : -0.4295493 
nnet RMSE 362 : 0.1501441 


s: 363 
logit 363 : -0.4265008 
logit mean 363 : -0.4264175 
logit RMSE 363 : 0.06871617 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 363 : -0.5245978 
boosting mean 363 : -0.501378 
boosting RMSE 363 : 0.159174 

forest 363 : -0.4563815 
forest mean 363 : -0.3808311 
forest RMSE 363 : 0.05397936 

nnet 363 : -0.1066137 
nnet mean 363 : -0.4286596 
nnet RMSE 363 : 0.1507258 


s: 364 
logit 364 : -0.4241291 
logit mean 364 : -0.4264113 
logit RMSE 364 : 0.06863337 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 364 : -0.6669713 
boosting mean 364 : -0.501833 
boosting RMSE 364 : 0.1595699 

forest 364 : -0.4275484 
forest mean 364 : -0.3809595 
forest RMSE 364 : 0.05392449 

nnet 364 : -0.4598945 
nnet mean 364 : -0.4287454 
nnet RMSE 364 : 0.1505513 


s: 365 
logit 365 : -0.4634983 
logit mean 365 : -0.4265129 
logit RMSE 365 : 0.06861983 

boosting 365 : -0.4169665 
boosting mean 365 : -0.5016005 
boosting RMSE 365 : 0.1593537 

forest 365 : -0.3693285 
forest mean 365 : -0.3809276 
forest RMSE 365 : 0.0538745 

nnet 365 : -0.2944019 
nnet mean 365 : -0.4283774 
nnet RMSE 365 : 0.1504465 


s: 366 
logit 366 : -0.4638228 
logit mean 366 : -0.4266148 
logit RMSE 366 : 0.06860718 

boosting 366 : -0.5283185 
boosting mean 366 : -0.5016735 
boosting RMSE 366 : 0.1592771 

forest 366 : -0.3350604 
forest mean 366 : -0.3808023 
forest RMSE 366 : 0.05390783 

nnet 366 : -0.4402546 
nnet mean 366 : -0.4284098 
nnet RMSE 366 : 0.1502556 


s: 367 
logit 367 : -0.3766650 
logit mean 367 : -0.4264787 
logit RMSE 367 : 0.06852447 

boosting 367 : -0.4656173 
boosting mean 367 : -0.5015752 
boosting RMSE 367 : 0.1590968 

forest 367 : -0.368043 
forest mean 367 : -0.3807675 
forest RMSE 367 : 0.05386017 

nnet 367 : -0.514121 
nnet mean 367 : -0.4286434 
nnet RMSE 367 : 0.1501689 


s: 368 
logit 368 : -0.4898122 
logit mean 368 : -0.4266508 
logit RMSE 368 : 0.06859127 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 368 : -0.5995996 
boosting mean 368 : -0.5018416 
boosting RMSE 368 : 0.1592209 

forest 368 : -0.4190387 
forest mean 368 : -0.3808715 
forest RMSE 368 : 0.0537961 

nnet 368 : -0.2348354 
nnet mean 368 : -0.4281167 
nnet RMSE 368 : 0.1502117 


s: 369 
logit 369 : -0.3811079 
logit mean 369 : -0.4265274 
logit RMSE 369 : 0.06850532 

boosting 369 : -0.6765411 
boosting mean 369 : -0.502315 
boosting RMSE 369 : 0.1596554 

forest 369 : -0.4016865 
forest mean 369 : -0.3809279 
forest RMSE 369 : 0.05372322 

nnet 369 : -0.4091649 
nnet mean 369 : -0.4280654 
nnet RMSE 369 : 0.1500088 


s: 370 
logit 370 : -0.4119796 
logit mean 370 : -0.4264881 
logit RMSE 370 : 0.06841552 

boosting 370 : -0.5594865 
boosting mean 370 : -0.5024695 
boosting RMSE 370 : 0.1596549 

forest 370 : -0.3333441 
forest mean 370 : -0.3807993 
forest RMSE 370 : 0.05376237 

nnet 370 : -0.3425883 
nnet mean 370 : -0.4278343 
nnet RMSE 370 : 0.1498357 


s: 371 
logit 371 : -0.4444569 
logit mean 371 : -0.4265365 
logit RMSE 371 : 0.06836223 

boosting 371 : -0.4166029 
boosting mean 371 : -0.5022381 
boosting RMSE 371 : 0.1594419 

forest 371 : -0.3445839 
forest mean 371 : -0.3807017 
forest RMSE 371 : 0.0537669 

nnet 371 : -0.2389314 
nnet mean 371 : -0.4273252 
nnet RMSE 371 : 0.1498671 


s: 372 
logit 372 : -0.3487856 
logit mean 372 : -0.4263275 
logit RMSE 372 : 0.0683219 

boosting 372 : -0.7499472 
boosting mean 372 : -0.502904 
boosting RMSE 372 : 0.1602579 

forest 372 : -0.3697105 
forest mean 372 : -0.3806721 
forest RMSE 372 : 0.05371754 

nnet 372 : -0.4359177 
nnet mean 372 : -0.4273483 
nnet RMSE 372 : 0.1496771 


s: 373 
logit 373 : -0.34472 
logit mean 373 : -0.4261087 
logit RMSE 373 : 0.06829027 

boosting 373 : -0.4582934 
boosting mean 373 : -0.5027844 
boosting RMSE 373 : 0.1600714 

forest 373 : -0.372259 
forest mean 373 : -0.3806496 
forest RMSE 373 : 0.05366471 

nnet 373 : -0.4134404 
nnet mean 373 : -0.427311 
nnet RMSE 373 : 0.1494780 


s: 374 
logit 374 : -0.4327879 
logit mean 374 : -0.4261266 
logit RMSE 374 : 0.06821998 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 374 : -0.4996965 
boosting mean 374 : -0.5027761 
boosting RMSE 374 : 0.1599403 

forest 374 : -0.3909459 
forest mean 374 : -0.3806771 
forest RMSE 374 : 0.05359496 

nnet 374 : -0.5893462 
nnet mean 374 : -0.4277442 
nnet RMSE 374 : 0.1495987 


s: 375 
logit 375 : -0.5064975 
logit mean 375 : -0.4263409 
logit RMSE 375 : 0.06835056 

boosting 375 : -0.3304748 
boosting mean 375 : -0.5023167 
boosting RMSE 375 : 0.1597673 

forest 375 : -0.3612173 
forest mean 375 : -0.3806252 
forest RMSE 375 : 0.05356091 

nnet 375 : -0.4922728 
nnet mean 375 : -0.4279163 
nnet RMSE 375 : 0.1494751 


s: 376 
logit 376 : -0.4644374 
logit mean 376 : -0.4264422 
logit RMSE 376 : 0.06834045 

boosting 376 : -0.7153491 
boosting mean 376 : -0.5028832 
boosting RMSE 376 : 0.1603814 

forest 376 : -0.3416026 
forest mean 376 : -0.3805214 
forest RMSE 376 : 0.05357435 

nnet 376 : -0.2642039 
nnet mean 376 : -0.4274809 
nnet RMSE 376 : 0.1494404 


s: 377 
logit 377 : -0.5260277 
logit mean 377 : -0.4267064 
logit RMSE 377 : 0.06855771 

boosting 377 : -0.61543 
boosting mean 377 : -0.5031818 
boosting RMSE 377 : 0.1605523 

forest 377 : -0.4217744 
forest mean 377 : -0.3806309 
forest RMSE 377 : 0.053515 

nnet 377 : -0.2136489 
nnet mean 377 : -0.4269137 
nnet RMSE 377 : 0.1495503 


s: 378 
logit 378 : -0.4645054 
logit mean 378 : -0.4268064 
logit RMSE 378 : 0.0685473 

boosting 378 : -0.6140118 
boosting mean 378 : -0.503475 
boosting RMSE 378 : 0.1607172 

forest 378 : -0.3770458 
forest mean 378 : -0.3806214 
forest RMSE 378 : 0.05345721 

nnet 378 : -0.5004196 
nnet mean 378 : -0.4271082 
nnet RMSE 378 : 0.1494417 


s: 379 
logit 379 : -0.372161 
logit mean 379 : -0.4266622 
logit RMSE 379 : 0.06847175 

boosting 379 : -0.4243803 
boosting mean 379 : -0.5032663 
boosting RMSE 379 : 0.1605099 

forest 379 : -0.4055838 
forest mean 379 : -0.3806873 
forest RMSE 379 : 0.05338741 

nnet 379 : -0.3389985 
nnet mean 379 : -0.4268757 
nnet RMSE 379 : 0.1492773 


s: 380 
logit 380 : -0.3483652 
logit mean 380 : -0.4264561 
logit RMSE 380 : 0.06843287 

boosting 380 : -0.3303288 
boosting mean 380 : -0.5028112 
boosting RMSE 380 : 0.1603384 

forest 380 : -0.3921007 
forest mean 380 : -0.3807173 
forest RMSE 380 : 0.05331866 

nnet 380 : -0.4333387 
nnet mean 380 : -0.4268927 
nnet RMSE 380 : 0.1490905 


s: 381 
logit 381 : -0.4996908 
logit mean 381 : -0.4266483 
logit RMSE 381 : 0.06853358 

boosting 381 : -0.502829 
boosting mean 381 : -0.5028112 
boosting RMSE 381 : 0.1602145 

forest 381 : -0.3543102 
forest mean 381 : -0.380648 
forest RMSE 381 : 0.05330006 

nnet 381 : -0.3449371 
nnet mean 381 : -0.4266776 
nnet RMSE 381 : 0.1489215 


s: 382 
logit 382 : -0.4147955 
logit mean 382 : -0.4266173 
logit RMSE 382 : 0.068448 

boosting 382 : -0.4702927 
boosting mean 382 : -0.5027261 
boosting RMSE 382 : 0.1600451 

forest 382 : -0.395206 
forest mean 382 : -0.3806861 
forest RMSE 382 : 0.05323082 

nnet 382 : -0.1796924 
nnet mean 382 : -0.426031 
nnet RMSE 382 : 0.1491530 


s: 383 
logit 383 : -0.4350013 
logit mean 383 : -0.4266392 
logit RMSE 383 : 0.06838198 

boosting 383 : -0.6228476 
boosting mean 383 : -0.5030397 
boosting RMSE 383 : 0.1602411 

forest 383 : -0.3587576 
forest mean 383 : -0.3806288 
forest RMSE 383 : 0.05320303 

nnet 383 : -0.4478019 
nnet mean 383 : -0.4260879 
nnet RMSE 383 : 0.1489781 


s: 384 
logit 384 : -0.3269336 
logit mean 384 : -0.4263796 
logit RMSE 384 : 0.0683946 

boosting 384 : -0.3523737 
boosting mean 384 : -0.5026474 
boosting RMSE 384 : 0.1600508 

forest 384 : -0.3535827 
forest mean 384 : -0.3805584 
forest RMSE 384 : 0.05318649 

nnet 384 : -0.5558317 
nnet mean 384 : -0.4264257 
nnet RMSE 384 : 0.1489964 


s: 385 
logit 385 : -0.4587682 
logit mean 385 : -0.4264637 
logit RMSE 385 : 0.06837135 

boosting 385 : -0.6532703 
boosting mean 385 : -0.5030386 
boosting RMSE 385 : 0.1603631 

forest 385 : -0.3747582 
forest mean 385 : -0.3805433 
forest RMSE 385 : 0.05313294 

nnet 385 : -0.3724559 
nnet mean 385 : -0.4262856 
nnet RMSE 385 : 0.1488094 


s: 386 
logit 386 : -0.436992 
logit mean 386 : -0.4264910 
logit RMSE 386 : 0.06830868 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 386 : -0.2464945 
boosting mean 386 : -0.502374 
boosting RMSE 386 : 0.1603457 

forest 386 : -0.4164334 
forest mean 386 : -0.3806363 
forest RMSE 386 : 0.05307067 

nnet 386 : -0.4571659 
nnet mean 386 : -0.4263656 
nnet RMSE 386 : 0.1486450 


s: 387 
logit 387 : -0.5090944 
logit mean 387 : -0.4267044 
logit RMSE 387 : 0.0684454 

boosting 387 : -0.5687956 
boosting mean 387 : -0.5025456 
boosting RMSE 387 : 0.1603682 

forest 387 : -0.433637 
forest mean 387 : -0.3807733 
forest RMSE 387 : 0.05302963 

nnet 387 : -0.8506225 
nnet mean 387 : -0.4274618 
nnet RMSE 387 : 0.1502097 


s: 388 
logit 388 : -0.3370262 
logit mean 388 : -0.4264733 
logit RMSE 388 : 0.06843185 

boosting 388 : -0.6974127 
boosting mean 388 : -0.5030478 
boosting RMSE 388 : 0.1608715 

forest 388 : -0.3701639 
forest mean 388 : -0.3807459 
forest RMSE 388 : 0.0529829 

nnet 388 : -0.8514724 
nnet mean 388 : -0.4285546 
nnet RMSE 388 : 0.1517568 


s: 389 
logit 389 : -0.3568162 
logit mean 389 : -0.4262942 
logit RMSE 389 : 0.0683789 

boosting 389 : -0.6815855 
boosting mean 389 : -0.5035068 
boosting RMSE 389 : 0.1612977 

forest 389 : -0.4927884 
forest mean 389 : -0.3810340 
forest RMSE 389 : 0.05312348 

nnet 389 : -0.5400559 
nnet mean 389 : -0.4288413 
nnet RMSE 389 : 0.1517278 


s: 390 
logit 390 : -0.3438707 
logit mean 390 : -0.4260829 
logit RMSE 390 : 0.0683503 

boosting 390 : -0.4229211 
boosting mean 390 : -0.5033002 
boosting RMSE 390 : 0.1610949 

forest 390 : -0.3673081 
forest mean 390 : -0.3809988 
forest RMSE 390 : 0.05308115 

nnet 390 : -0.2825335 
nnet mean 390 : -0.4284661 
nnet RMSE 390 : 0.1516499 


s: 391 
logit 391 : -0.3568395 
logit mean 391 : -0.4259058 
logit RMSE 391 : 0.06829773 

boosting 391 : -0.2674125 
boosting mean 391 : -0.5026969 
boosting RMSE 391 : 0.1610285 

forest 391 : -0.3133186 
forest mean 391 : -0.3808257 
forest RMSE 391 : 0.05319416 

nnet 391 : -0.4005632 
nnet mean 391 : -0.4283948 
nnet RMSE 391 : 0.1514558 


s: 392 
logit 392 : -0.5756522 
logit mean 392 : -0.4262878 
logit RMSE 392 : 0.06878509 

boosting 392 : -0.4739278 
boosting mean 392 : -0.5026235 
boosting RMSE 392 : 0.1608663 

forest 392 : -0.4283718 
forest mean 392 : -0.3809470 
forest RMSE 392 : 0.0531456 

nnet 392 : -0.4795282 
nnet mean 392 : -0.4285252 
nnet RMSE 392 : 0.1513159 


s: 393 
logit 393 : -0.4033643 
logit mean 393 : -0.4262294 
logit RMSE 393 : 0.06869773 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 393 : -0.4946167 
boosting mean 393 : -0.5026031 
boosting RMSE 393 : 0.1607324 

forest 393 : -0.4340587 
forest mean 393 : -0.3810821 
forest RMSE 393 : 0.05310573 

nnet 393 : -0.4061562 
nnet mean 393 : -0.4284683 
nnet RMSE 393 : 0.1511235 


s: 394 
logit 394 : -0.3529993 
logit mean 394 : -0.4260436 
logit RMSE 394 : 0.06865134 

boosting 394 : -0.4267712 
boosting mean 394 : -0.5024107 
boosting RMSE 394 : 0.1605339 

forest 394 : -0.3883696 
forest mean 394 : -0.3811006 
forest RMSE 394 : 0.05304153 

nnet 394 : -0.5860555 
nnet mean 394 : -0.4288683 
nnet RMSE 394 : 0.1512224 


s: 395 
logit 395 : -0.4432279 
logit mean 395 : -0.4260871 
logit RMSE 395 : 0.06859888 

boosting 395 : -0.5868386 
boosting mean 395 : -0.5026244 
boosting RMSE 395 : 0.1606059 

forest 395 : -0.3214039 
forest mean 395 : -0.3809495 
forest RMSE 395 : 0.05312175 

nnet 395 : -0.5009284 
nnet mean 395 : -0.4290507 
nnet RMSE 395 : 0.1511162 


s: 396 
logit 396 : -0.4473366 
logit mean 396 : -0.4261407 
logit RMSE 396 : 0.06855349 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 396 : -0.5984398 
boosting mean 396 : -0.5028664 
boosting RMSE 396 : 0.1607127 

forest 396 : -0.3896104 
forest mean 396 : -0.3809713 
forest RMSE 396 : 0.05305721 

nnet 396 : -0.491777 
nnet mean 396 : -0.4292091 
nnet RMSE 396 : 0.1509958 


s: 397 
logit 397 : -0.4449257 
logit mean 397 : -0.4261881 
logit RMSE 397 : 0.06850421 

boosting 397 : -0.4365719 
boosting mean 397 : -0.5026994 
boosting RMSE 397 : 0.1605207 

forest 397 : -0.4071969 
forest mean 397 : -0.3810374 
forest RMSE 397 : 0.05299157 

nnet 397 : -0.5443165 
nnet mean 397 : -0.429499 
nnet RMSE 397 : 0.1509793 


s: 398 
logit 398 : -0.3610985 
logit mean 398 : -0.4260245 
logit RMSE 398 : 0.06844588 

boosting 398 : -0.5401887 
boosting mean 398 : -0.5027936 
boosting RMSE 398 : 0.1604728 

forest 398 : -0.3715619 
forest mean 398 : -0.3810136 
forest RMSE 398 : 0.05294415 

nnet 398 : -0.5203808 
nnet mean 398 : -0.4297274 
nnet RMSE 398 : 0.1509102 


s: 399 
logit 399 : -0.4997984 
logit mean 399 : -0.4262094 
logit RMSE 399 : 0.06854239 

boosting 399 : -0.6570373 
boosting mean 399 : -0.5031801 
boosting RMSE 399 : 0.1607873 

forest 399 : -0.4628038 
forest mean 399 : -0.3812186 
forest RMSE 399 : 0.05297116 

nnet 399 : -0.4072203 
nnet mean 399 : -0.429671 
nnet RMSE 399 : 0.1507214 


s: 400 
logit 400 : -0.5019416 
logit mean 400 : -0.4263988 
logit RMSE 400 : 0.06864615 

boosting 400 : -0.6411713 
boosting mean 400 : -0.5035251 
boosting RMSE 400 : 0.1610383 

forest 400 : -0.3711799 
forest mean 400 : -0.3811935 
forest RMSE 400 : 0.05292452 

nnet 400 : -0.06089111 
nnet mean 400 : -0.428749 
nnet RMSE 400 : 0.1514848 


s: 401 
logit 401 : -0.4937383 
logit mean 401 : -0.4265667 
logit RMSE 401 : 0.06872012 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 401 : -0.705927 
boosting mean 401 : -0.5040299 
boosting RMSE 401 : 0.1615613 

forest 401 : -0.320226 
forest mean 401 : -0.3810414 
forest RMSE 401 : 0.0530084 

nnet 401 : -0.4614626 
nnet mean 401 : -0.4288306 
nnet RMSE 401 : 0.1513269 


s: 402 
logit 402 : -0.4435346 
logit mean 402 : -0.4266089 
logit RMSE 402 : 0.06866893 

boosting 402 : -0.5077901 
boosting mean 402 : -0.5040392 
boosting RMSE 402 : 0.1614498 

forest 402 : -0.2841346 
forest mean 402 : -0.3808004 
forest RMSE 402 : 0.05325688 

nnet 402 : -0.2863676 
nnet mean 402 : -0.4284762 
nnet RMSE 402 : 0.1512448 


s: 403 
logit 403 : -0.4052021 
logit mean 403 : -0.4265558 
logit RMSE 403 : 0.06858417 

boosting 403 : -0.5705401 
boosting mean 403 : -0.5042042 
boosting RMSE 403 : 0.161473 

forest 403 : -0.323526 
forest mean 403 : -0.3806583 
forest RMSE 403 : 0.053327 

nnet 403 : -0.4929046 
nnet mean 403 : -0.4286361 
nnet RMSE 403 : 0.1511279 


s: 404 
logit 404 : -0.5378111 
logit mean 404 : -0.4268312 
logit RMSE 404 : 0.06884152 

boosting 404 : -0.6384198 
boosting mean 404 : -0.5045364 
boosting RMSE 404 : 0.1617087 

forest 404 : -0.4370137 
forest mean 404 : -0.3807977 
forest RMSE 404 : 0.05329279 

nnet 404 : -0.1104853 
nnet mean 404 : -0.4278486 
nnet RMSE 404 : 0.1516264 


s: 405 
logit 405 : -0.3020739 
logit mean 405 : -0.4265231 
logit RMSE 405 : 0.06892845 

boosting 405 : -0.2390007 
boosting mean 405 : -0.5038808 
boosting RMSE 405 : 0.1617069 

forest 405 : -0.390059 
forest mean 405 : -0.3808206 
forest RMSE 405 : 0.05322925 

nnet 405 : -0.2945022 
nnet mean 405 : -0.4275193 
nnet RMSE 405 : 0.1515298 


s: 406 
logit 406 : -0.3864039 
logit mean 406 : -0.4264243 
logit RMSE 406 : 0.06884682 

boosting 406 : -0.3491361 
boosting mean 406 : -0.5034997 
boosting RMSE 406 : 0.1615274 

forest 406 : -0.3291624 
forest mean 406 : -0.3806934 
forest RMSE 406 : 0.05327977 

nnet 406 : -0.5370293 
nnet mean 406 : -0.4277891 
nnet RMSE 406 : 0.1514958 


s: 407 
logit 407 : -0.4629656 
logit mean 407 : -0.4265141 
logit RMSE 407 : 0.06883298 

boosting 407 : -0.5449675 
boosting mean 407 : -0.5036015 
boosting RMSE 407 : 0.1614888 

forest 407 : -0.4510693 
forest mean 407 : -0.3808663 
forest RMSE 407 : 0.05327445 

nnet 407 : -0.5321433 
nnet mean 407 : -0.4280455 
nnet RMSE 407 : 0.1514513 


s: 408 
logit 408 : -0.4602658 
logit mean 408 : -0.4265968 
logit RMSE 408 : 0.06881329 

boosting 408 : -0.486267 
boosting mean 408 : -0.5035591 
boosting RMSE 408 : 0.1613473 

forest 408 : -0.4549983 
forest mean 408 : -0.381048 
forest RMSE 408 : 0.05327874 

nnet 408 : -0.7043187 
nnet mean 408 : -0.4287226 
nnet RMSE 408 : 0.1520140 


s: 409 
logit 409 : -0.3429738 
logit mean 409 : -0.4263923 
logit RMSE 409 : 0.06878693 

boosting 409 : -0.6162279 
boosting mean 409 : -0.5038345 
boosting RMSE 409 : 0.1615042 

forest 409 : -0.4084657 
forest mean 409 : -0.381115 
forest RMSE 409 : 0.05321521 

nnet 409 : -0.1581483 
nnet mean 409 : -0.4280611 
nnet RMSE 409 : 0.1522983 


s: 410 
logit 410 : -0.3646178 
logit mean 410 : -0.4262417 
logit RMSE 410 : 0.06872521 

boosting 410 : -0.4162915 
boosting mean 410 : -0.503621 
boosting RMSE 410 : 0.1613091 

forest 410 : -0.3955027 
forest mean 410 : -0.3811501 
forest RMSE 410 : 0.05315074 

nnet 410 : -0.09583772 
nnet mean 410 : -0.4272507 
nnet RMSE 410 : 0.1528524 


s: 411 
logit 411 : -0.4822347 
logit mean 411 : -0.4263779 
logit RMSE 411 : 0.0687613 

boosting 411 : -0.4776693 
boosting mean 411 : -0.5035579 
boosting RMSE 411 : 0.1611583 

forest 411 : -0.3750543 
forest mean 411 : -0.3811353 
forest RMSE 411 : 0.0531003 

nnet 411 : -0.3083899 
nnet mean 411 : -0.4269616 
nnet RMSE 411 : 0.1527332 


s: 412 
logit 412 : -0.3687509 
logit mean 412 : -0.426238 
logit RMSE 412 : 0.06869506 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 412 : -0.2613022 
boosting mean 412 : -0.5029699 
boosting RMSE 412 : 0.1611076 

forest 412 : -0.2767805 
forest mean 412 : -0.380882 
forest RMSE 412 : 0.05338212 

nnet 412 : -0.228976 
nnet mean 412 : -0.426481 
nnet RMSE 412 : 0.1527802 


s: 413 
logit 413 : -0.436027 
logit mean 413 : -0.4262617 
logit RMSE 413 : 0.06863474 

boosting 413 : -0.3996169 
boosting mean 413 : -0.5027196 
boosting RMSE 413 : 0.1609124 

forest 413 : -0.3948228 
forest mean 413 : -0.3809158 
forest RMSE 413 : 0.05331806 

nnet 413 : -0.314409 
nnet mean 413 : -0.4262096 
nnet RMSE 413 : 0.1526533 


s: 414 
logit 414 : -0.3750268 
logit mean 414 : -0.426138 
logit RMSE 414 : 0.06856279 

boosting 414 : -0.4496656 
boosting mean 414 : -0.5025915 
boosting RMSE 414 : 0.1607365 

forest 414 : -0.2805328 
forest mean 414 : -0.3806733 
forest RMSE 414 : 0.05357633 

nnet 414 : -0.4423568 
nnet mean 414 : -0.4262486 
nnet RMSE 414 : 0.152483 


s: 415 
logit 415 : -0.4423221 
logit mean 415 : -0.426177 
logit RMSE 415 : 0.06851164 

boosting 415 : -0.577773 
boosting mean 415 : -0.5027726 
boosting RMSE 415 : 0.1607797 

forest 415 : -0.4118876 
forest mean 415 : -0.3807485 
forest RMSE 415 : 0.05351492 

nnet 415 : -0.6084447 
nnet mean 415 : -0.4266877 
nnet RMSE 415 : 0.1526425 


s: 416 
logit 416 : -0.3952344 
logit mean 416 : -0.4261026 
logit RMSE 416 : 0.06842964 

boosting 416 : -0.5113837 
boosting mean 416 : -0.5027933 
boosting RMSE 416 : 0.1606792 

forest 416 : -0.2624507 
forest mean 416 : -0.3804641 
forest RMSE 416 : 0.05387433 

nnet 416 : -0.697565 
nnet mean 416 : -0.4273388 
nnet RMSE 416 : 0.1531554 


s: 417 
logit 417 : -0.4194622 
logit mean 417 : -0.4260867 
logit RMSE 417 : 0.06835419 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 417 : -0.6307272 
boosting mean 417 : -0.5031001 
boosting RMSE 417 : 0.1608837 

forest 417 : -0.3384223 
forest mean 417 : -0.3803633 
forest RMSE 417 : 0.05389412 

nnet 417 : -0.7049646 
nnet mean 417 : -0.4280046 
nnet RMSE 417 : 0.1536989 


s: 418 
logit 418 : -0.4248375 
logit mean 418 : -0.4260837 
logit RMSE 418 : 0.06828318 

boosting 418 : -0.6366838 
boosting mean 418 : -0.5034197 
boosting RMSE 418 : 0.1611076 

forest 418 : -0.4303072 
forest mean 418 : -0.3804828 
forest RMSE 418 : 0.05385002 

nnet 418 : -0.5857784 
nnet mean 418 : -0.428382 
nnet RMSE 418 : 0.1537836 


s: 419 
logit 419 : -0.5093189 
logit mean 419 : -0.4262823 
logit RMSE 419 : 0.06841043 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 419 : -0.6987355 
boosting mean 419 : -0.5038858 
boosting RMSE 419 : 0.1615757 

forest 419 : -0.3604363 
forest mean 419 : -0.3804349 
forest RMSE 419 : 0.05382044 

nnet 419 : -0.5628797 
nnet mean 419 : -0.428703 
nnet RMSE 419 : 0.153806 


s: 420 
logit 420 : -0.428141 
logit mean 420 : -0.4262868 
logit RMSE 420 : 0.06834273 

boosting 420 : -0.557484 
boosting mean 420 : -0.5040135 
boosting RMSE 420 : 0.1615660 

forest 420 : -0.3633988 
forest mean 420 : -0.3803944 
forest RMSE 420 : 0.05378599 

nnet 420 : -0.3306452 
nnet mean 420 : -0.4284696 
nnet RMSE 420 : 0.1536600 


s: 421 
logit 421 : -0.3181039 
logit mean 421 : -0.4260298 
logit RMSE 421 : 0.06837811 

boosting 421 : -0.4730459 
boosting mean 421 : -0.5039399 
boosting RMSE 421 : 0.1614133 

forest 421 : -0.3256752 
forest mean 421 : -0.3802644 
forest RMSE 421 : 0.05384405 

nnet 421 : -0.1266070 
nnet mean 421 : -0.4277525 
nnet RMSE 421 : 0.1540547 


s: 422 
logit 422 : -0.4422813 
logit mean 422 : -0.4260683 
logit RMSE 422 : 0.06832805 

boosting 422 : -0.5377576 
boosting mean 422 : -0.50402 
boosting RMSE 422 : 0.1613613 

forest 422 : -0.3268104 
forest mean 422 : -0.3801377 
forest RMSE 422 : 0.0538981 

nnet 422 : -0.504864 
nnet mean 422 : -0.4279353 
nnet RMSE 422 : 0.1539568 


s: 423 
logit 423 : -0.413619 
logit mean 423 : -0.4260389 
logit RMSE 423 : 0.06825045 

boosting 423 : -0.4537697 
boosting mean 423 : -0.5039012 
boosting RMSE 423 : 0.1611917 

forest 423 : -0.4323966 
forest mean 423 : -0.3802613 
forest RMSE 423 : 0.0538574 

nnet 423 : -0.5523435 
nnet mean 423 : -0.4282294 
nnet RMSE 423 : 0.1539530 


s: 424 
logit 424 : -0.4494379 
logit mean 424 : -0.4260941 
logit RMSE 424 : 0.06821219 

boosting 424 : -0.5194213 
boosting mean 424 : -0.5039378 
boosting RMSE 424 : 0.1611059 

forest 424 : -0.3985821 
forest mean 424 : -0.3803045 
forest RMSE 424 : 0.05379389 

nnet 424 : -0.5553423 
nnet mean 424 : -0.4285292 
nnet RMSE 424 : 0.1539563 


s: 425 
logit 425 : -0.4186661 
logit mean 425 : -0.4260766 
logit RMSE 425 : 0.0681379 

boosting 425 : -0.4404317 
boosting mean 425 : -0.5037884 
boosting RMSE 425 : 0.1609282 

forest 425 : -0.394885 
forest mean 425 : -0.3803388 
forest RMSE 425 : 0.05373114 

nnet 425 : -0.5316431 
nnet mean 425 : -0.4287718 
nnet RMSE 425 : 0.1539076 


s: 426 
logit 426 : -0.421055 
logit mean 426 : -0.4260648 
logit RMSE 426 : 0.06806553 

boosting 426 : -0.4891291 
boosting mean 426 : -0.503754 
boosting RMSE 426 : 0.1607972 

forest 426 : -0.3304294 
forest mean 426 : -0.3802216 
forest RMSE 426 : 0.05377379 

nnet 426 : -0.6305066 
nnet mean 426 : -0.4292454 
nnet RMSE 426 : 0.1541319 


s: 427 
logit 427 : -0.4507393 
logit mean 427 : -0.4261226 
logit RMSE 427 : 0.06803011 

boosting 427 : -0.2842093 
boosting mean 427 : -0.5032399 
boosting RMSE 427 : 0.1607066 

forest 427 : -0.355615 
forest mean 427 : -0.380164 
forest RMSE 427 : 0.05375372 

nnet 427 : -0.2732645 
nnet mean 427 : -0.4288801 
nnet RMSE 427 : 0.1540735 


s: 428 
logit 428 : -0.4844741 
logit mean 428 : -0.4262589 
logit RMSE 428 : 0.06807316 

boosting 428 : -0.4620757 
boosting mean 428 : -0.5031437 
boosting RMSE 428 : 0.1605467 

forest 428 : -0.370925 
forest mean 428 : -0.3801424 
forest RMSE 428 : 0.05370927 

nnet 428 : -0.2895250 
nnet mean 428 : -0.4285545 
nnet RMSE 428 : 0.153986 


s: 429 
logit 429 : -0.4277996 
logit mean 429 : -0.4262625 
logit RMSE 429 : 0.06800702 

boosting 429 : -0.4788338 
boosting mean 429 : -0.503087 
boosting RMSE 429 : 0.1604047 

forest 429 : -0.3844024 
forest mean 429 : -0.3801524 
forest RMSE 429 : 0.05365192 

nnet 429 : -0.5917385 
nnet mean 429 : -0.4289349 
nnet RMSE 429 : 0.1540848 


s: 430 
logit 430 : -0.3251158 
logit mean 430 : -0.4260273 
logit RMSE 430 : 0.06802382 

boosting 430 : -0.4713619 
boosting mean 430 : -0.5030132 
boosting RMSE 430 : 0.160255 

forest 430 : -0.3638890 
forest mean 430 : -0.3801145 
forest RMSE 430 : 0.05361779 

nnet 430 : -0.272039 
nnet mean 430 : -0.42857 
nnet RMSE 430 : 0.1540291 


s: 431 
logit 431 : -0.4583658 
logit mean 431 : -0.4261023 
logit RMSE 431 : 0.068003 

boosting 431 : -0.5852442 
boosting mean 431 : -0.503204 
boosting RMSE 431 : 0.1603175 

forest 431 : -0.3031005 
forest mean 431 : -0.3799359 
forest RMSE 431 : 0.05375856 

nnet 431 : -0.502422 
nnet mean 431 : -0.4287413 
nnet RMSE 431 : 0.1539294 


s: 432 
logit 432 : -0.3340969 
logit mean 432 : -0.4258893 
logit RMSE 432 : 0.06799821 

boosting 432 : -0.5043386 
boosting mean 432 : -0.5032066 
boosting RMSE 432 : 0.1602105 

forest 432 : -0.3302062 
forest mean 432 : -0.3798207 
forest RMSE 432 : 0.05380119 

nnet 432 : -0.4201743 
nnet mean 432 : -0.4287215 
nnet RMSE 432 : 0.1537542 


s: 433 
logit 433 : -0.4273628 
logit mean 433 : -0.4258927 
logit RMSE 433 : 0.06793237 

boosting 433 : -0.6580933 
boosting mean 433 : -0.5035644 
boosting RMSE 433 : 0.1605053 

forest 433 : -0.3833105 
forest mean 433 : -0.3798288 
forest RMSE 433 : 0.05374502 

nnet 433 : -0.5145437 
nnet mean 433 : -0.4289197 
nnet RMSE 433 : 0.1536752 


s: 434 
logit 434 : -0.4822414 
logit mean 434 : -0.4260226 
logit RMSE 434 : 0.06796881 

boosting 434 : -0.4756211 
boosting mean 434 : -0.5035 
boosting RMSE 434 : 0.1603614 

forest 434 : -0.3861766 
forest mean 434 : -0.3798434 
forest RMSE 434 : 0.05368716 

nnet 434 : -0.4719969 
nnet mean 434 : -0.4290190 
nnet RMSE 434 : 0.1535370 


s: 435 
logit 435 : -0.5158766 
logit mean 435 : -0.4262291 
logit RMSE 435 : 0.06811759 

boosting 435 : -0.2989957 
boosting mean 435 : -0.5030298 
boosting RMSE 435 : 0.1602502 

forest 435 : -0.4116017 
forest mean 435 : -0.3799164 
forest RMSE 435 : 0.0536283 

nnet 435 : -0.3563147 
nnet mean 435 : -0.4288518 
nnet RMSE 435 : 0.1533747 


s: 436 
logit 436 : -0.3450902 
logit mean 436 : -0.4260430 
logit RMSE 436 : 0.06809023 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 436 : -0.5019866 
boosting mean 436 : -0.5030275 
boosting RMSE 436 : 0.1601408 

forest 436 : -0.4374933 
forest mean 436 : -0.3800485 
forest RMSE 436 : 0.05359685 

nnet 436 : -0.4572455 
nnet mean 436 : -0.4289169 
nnet RMSE 436 : 0.1532232 


s: 437 
logit 437 : -0.3906043 
logit mean 437 : -0.4259620 
logit RMSE 437 : 0.06801376 

boosting 437 : -0.5355712 
boosting mean 437 : -0.5031019 
boosting RMSE 437 : 0.1600889 

forest 437 : -0.4459786 
forest mean 437 : -0.3801994 
forest RMSE 437 : 0.05358066 

nnet 437 : -0.4286502 
nnet mean 437 : -0.4289163 
nnet RMSE 437 : 0.1530539 


s: 438 
logit 438 : -0.3825044 
logit mean 438 : -0.4258627 
logit RMSE 438 : 0.06794122 

boosting 438 : -0.6015763 
boosting mean 438 : -0.5033267 
boosting RMSE 438 : 0.1601958 

forest 438 : -0.2577123 
forest mean 438 : -0.3799197 
forest RMSE 438 : 0.05394957 

nnet 438 : -0.4662237 
nnet mean 438 : -0.4290015 
nnet RMSE 438 : 0.1529119 


s: 439 
logit 439 : -0.40272 
logit mean 439 : -0.42581 
logit RMSE 439 : 0.06786392 

boosting 439 : -0.4500515 
boosting mean 439 : -0.5032054 
boosting RMSE 439 : 0.1600311 

forest 439 : -0.4179866 
forest mean 439 : -0.3800064 
forest RMSE 439 : 0.05389492 

nnet 439 : -0.3928298 
nnet mean 439 : -0.4289191 
nnet RMSE 439 : 0.152738 


s: 440 
logit 440 : -0.4863208 
logit mean 440 : -0.4259475 
logit RMSE 440 : 0.06791155 

boosting 440 : -0.4083919 
boosting mean 440 : -0.5029899 
boosting RMSE 440 : 0.1598497 

forest 440 : -0.5303071 
forest mean 440 : -0.380348 
forest RMSE 440 : 0.05419088 

nnet 440 : -0.4635209 
nnet mean 440 : -0.4289978 
nnet RMSE 440 : 0.1525944 


s: 441 
logit 441 : -0.462547 
logit mean 441 : -0.4260305 
logit RMSE 441 : 0.06789987 

boosting 441 : -0.5418549 
boosting mean 441 : -0.503078 
boosting RMSE 441 : 0.1598111 

forest 441 : -0.3289971 
forest mean 441 : -0.3802316 
forest RMSE 441 : 0.0542349 

nnet 441 : -0.6222447 
nnet mean 441 : -0.4294360 
nnet RMSE 441 : 0.1527882 


s: 442 
logit 442 : -0.4628638 
logit mean 442 : -0.4261139 
logit RMSE 442 : 0.0678889 

boosting 442 : -0.6199214 
boosting mean 442 : -0.5033424 
boosting RMSE 442 : 0.1599726 

forest 442 : -0.3683361 
forest mean 442 : -0.3802047 
forest RMSE 442 : 0.05419445 

nnet 442 : -0.5147794 
nnet mean 442 : -0.429629 
nnet RMSE 442 : 0.1527129 


s: 443 
logit 443 : -0.3934804 
logit mean 443 : -0.4260402 
logit RMSE 443 : 0.06781294 

boosting 443 : -0.8809175 
boosting mean 443 : -0.5041947 
boosting RMSE 443 : 0.1614173 

forest 443 : -0.3545598 
forest mean 443 : -0.3801468 
forest RMSE 443 : 0.05417628 

nnet 443 : -0.4909158 
nnet mean 443 : -0.4297674 
nnet RMSE 443 : 0.1526016 


s: 444 
logit 444 : -0.4013584 
logit mean 444 : -0.4259846 
logit RMSE 444 : 0.06773656 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 444 : -0.4353394 
boosting mean 444 : -0.5040396 
boosting RMSE 444 : 0.1612442 

forest 444 : -0.3296056 
forest mean 444 : -0.3800329 
forest RMSE 444 : 0.05421826 

nnet 444 : -0.4934482 
nnet mean 444 : -0.4299108 
nnet RMSE 444 : 0.1524942 


s: 445 
logit 445 : -0.3324003 
logit mean 445 : -0.4257743 
logit RMSE 445 : 0.06773625 

boosting 445 : -0.7437606 
boosting mean 445 : -0.5045783 
boosting RMSE 445 : 0.1618852 

forest 445 : -0.2569484 
forest mean 445 : -0.3797563 
forest RMSE 445 : 0.05458021 

nnet 445 : -0.2178796 
nnet mean 445 : -0.4294343 
nnet RMSE 445 : 0.1525672 


s: 446 
logit 446 : -0.4549802 
logit mean 446 : -0.4258398 
logit RMSE 446 : 0.06771034 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 446 : -0.5270226 
boosting mean 446 : -0.5046286 
boosting RMSE 446 : 0.1618154 

forest 446 : -0.4545057 
forest mean 446 : -0.3799239 
forest RMSE 446 : 0.05458004 

nnet 446 : -0.3599905 
nnet mean 446 : -0.4292786 
nnet RMSE 446 : 0.1524078 


s: 447 
logit 447 : -0.2447308 
logit mean 447 : -0.4254346 
logit RMSE 447 : 0.0680321 

boosting 447 : -0.4960009 
boosting mean 447 : -0.5046093 
boosting RMSE 447 : 0.1616981 

forest 447 : -0.3599739 
forest mean 447 : -0.3798793 
forest RMSE 447 : 0.05455182 

nnet 447 : -0.3384455 
nnet mean 447 : -0.4290754 
nnet RMSE 447 : 0.1522651 


s: 448 
logit 448 : -0.5206699 
logit mean 448 : -0.4256472 
logit RMSE 448 : 0.06819486 

boosting 448 : -0.4615785 
boosting mean 448 : -0.5045133 
boosting RMSE 448 : 0.1615437 

forest 448 : -0.3866565 
forest mean 448 : -0.3798944 
forest RMSE 448 : 0.05449455 

nnet 448 : -0.5244781 
nnet mean 448 : -0.4292884 
nnet RMSE 448 : 0.1522087 


s: 449 
logit 449 : -0.5138657 
logit mean 449 : -0.4258437 
logit RMSE 449 : 0.0683305 

boosting 449 : -0.6564288 
boosting mean 449 : -0.5048516 
boosting RMSE 449 : 0.1618169 

forest 449 : -0.3487453 
forest mean 449 : -0.3798251 
forest RMSE 449 : 0.05448755 

nnet 449 : -0.337756 
nnet mean 449 : -0.4290845 
nnet RMSE 449 : 0.1520675 


s: 450 
logit 450 : -0.4506598 
logit mean 450 : -0.4258988 
logit RMSE 450 : 0.0682963 

boosting 450 : -0.7831927 
boosting mean 450 : -0.5054702 
boosting RMSE 450 : 0.1626432 

forest 450 : -0.4161299 
forest mean 450 : -0.3799057 
forest RMSE 450 : 0.05443228 

nnet 450 : -0.6174156 
nnet mean 450 : -0.429503 
nnet RMSE 450 : 0.1522438 


s: 451 
logit 451 : -0.4393522 
logit mean 451 : -0.4259287 
logit RMSE 451 : 0.0682457 

boosting 451 : -0.4125912 
boosting mean 451 : -0.5052642 
boosting RMSE 451 : 0.1624639 

forest 451 : -0.4485332 
forest mean 451 : -0.3800579 
forest RMSE 451 : 0.05441991 

nnet 451 : -0.5505215 
nnet mean 451 : -0.4297714 
nnet RMSE 451 : 0.1522400 


s: 452 
logit 452 : -0.4101395 
logit mean 452 : -0.4258937 
logit RMSE 452 : 0.06817184 

boosting 452 : -0.6249167 
boosting mean 452 : -0.5055289 
boosting RMSE 452 : 0.1626285 

forest 452 : -0.3712008 
forest mean 452 : -0.3800383 
forest RMSE 452 : 0.05437655 

nnet 452 : -0.4089678 
nnet mean 452 : -0.4297253 
nnet RMSE 452 : 0.1520721 


s: 453 
logit 453 : -0.4069945 
logit mean 453 : -0.425852 
logit RMSE 453 : 0.06809735 

boosting 453 : -0.4029158 
boosting mean 453 : -0.5053024 
boosting RMSE 453 : 0.1624490 

forest 453 : -0.3290187 
forest mean 453 : -0.3799257 
forest RMSE 453 : 0.05441879 

nnet 453 : -0.5522945 
nnet mean 453 : -0.4299959 
nnet RMSE 453 : 0.1520726 


s: 454 
logit 454 : -0.3317628 
logit mean 454 : -0.4256448 
logit RMSE 454 : 0.06809765 

boosting 454 : -0.3495064 
boosting mean 454 : -0.5049593 
boosting RMSE 454 : 0.1622873 

forest 454 : -0.3142142 
forest mean 454 : -0.3797809 
forest RMSE 454 : 0.05450772 

nnet 454 : -0.3884559 
nnet mean 454 : -0.4299044 
nnet RMSE 454 : 0.151906 


s: 455 
logit 455 : -0.478409 
logit mean 455 : -0.4257607 
logit RMSE 455 : 0.06812203 

boosting 455 : -0.472044 
boosting mean 455 : -0.5048869 
boosting RMSE 455 : 0.1621440 

forest 455 : -0.373211 
forest mean 455 : -0.3797665 
forest RMSE 455 : 0.05446227 

nnet 455 : -0.3585229 
nnet mean 455 : -0.4297475 
nnet RMSE 455 : 0.1517514 


s: 456 
logit 456 : -0.4597794 
logit mean 456 : -0.4258353 
logit RMSE 456 : 0.06810485 

boosting 456 : -0.3542348 
boosting mean 456 : -0.5045565 
boosting RMSE 456 : 0.1619803 

forest 456 : -0.4048519 
forest mean 456 : -0.3798215 
forest RMSE 456 : 0.05440299 

nnet 456 : -0.3547283 
nnet mean 456 : -0.429583 
nnet RMSE 456 : 0.1515998 


s: 457 
logit 457 : -0.4211657 
logit mean 457 : -0.4258251 
logit RMSE 457 : 0.0680375 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 457 : -0.5302603 
boosting mean 457 : -0.5046128 
boosting RMSE 457 : 0.1619177 

forest 457 : -0.3527818 
forest mean 457 : -0.3797624 
forest RMSE 457 : 0.05438831 

nnet 457 : -0.4511358 
nnet mean 457 : -0.4296302 
nnet RMSE 457 : 0.1514527 


s: 458 
logit 458 : -0.3180522 
logit mean 458 : -0.4255898 
logit RMSE 458 : 0.06807097 

boosting 458 : -0.4304576 
boosting mean 458 : -0.5044509 
boosting RMSE 458 : 0.1617471 

forest 458 : -0.3292285 
forest mean 458 : -0.379652 
forest RMSE 458 : 0.05442945 

nnet 458 : -0.5631333 
nnet mean 458 : -0.4299217 
nnet RMSE 458 : 0.1514792 


s: 459 
logit 459 : -0.5157947 
logit mean 459 : -0.4257863 
logit RMSE 459 : 0.06821125 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 459 : -0.6374659 
boosting mean 459 : -0.5047407 
boosting RMSE 459 : 0.1619505 

forest 459 : -0.3461363 
forest mean 459 : -0.379579 
forest RMSE 459 : 0.05442822 

nnet 459 : -0.4265038 
nnet mean 459 : -0.4299142 
nnet RMSE 459 : 0.1513191 


s: 460 
logit 460 : -0.3768992 
logit mean 460 : -0.4256801 
logit RMSE 460 : 0.06814558 

boosting 460 : -0.5773988 
boosting mean 460 : -0.5048986 
boosting RMSE 460 : 0.1619857 

forest 460 : -0.3870265 
forest mean 460 : -0.3795952 
forest RMSE 460 : 0.0543724 

nnet 460 : -0.5291806 
nnet mean 460 : -0.43013 
nnet RMSE 460 : 0.1512745 


s: 461 
logit 461 : -0.4026223 
logit mean 461 : -0.42563 
logit RMSE 461 : 0.06807173 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 461 : -0.634495 
boosting mean 461 : -0.5051797 
boosting RMSE 461 : 0.1621781 

forest 461 : -0.4330098 
forest mean 461 : -0.3797111 
forest RMSE 461 : 0.05433515 

nnet 461 : -0.5535557 
nnet mean 461 : -0.4303978 
nnet RMSE 461 : 0.1512795 


s: 462 
logit 462 : -0.4504853 
logit mean 462 : -0.4256838 
logit RMSE 462 : 0.06803858 

boosting 462 : -0.4283905 
boosting mean 462 : -0.5050135 
boosting RMSE 462 : 0.1620079 

forest 462 : -0.3455731 
forest mean 462 : -0.3796372 
forest RMSE 462 : 0.05433534 

nnet 462 : -0.3172569 
nnet mean 462 : -0.4301529 
nnet RMSE 462 : 0.1511647 


s: 463 
logit 463 : -0.4643822 
logit mean 463 : -0.4257674 
logit RMSE 463 : 0.06803089 

boosting 463 : -0.5752082 
boosting mean 463 : -0.5051651 
boosting RMSE 463 : 0.1620375 

forest 463 : -0.4418576 
forest mean 463 : -0.3797715 
forest RMSE 463 : 0.05431148 

nnet 463 : -0.4854281 
nnet mean 463 : -0.4302722 
nnet RMSE 463 : 0.1510536 


s: 464 
logit 464 : -0.2996946 
logit mean 464 : -0.4254957 
logit RMSE 464 : 0.0681169 

boosting 464 : -0.4550559 
boosting mean 464 : -0.5050572 
boosting RMSE 464 : 0.161883 

forest 464 : -0.3673480 
forest mean 464 : -0.3797448 
forest RMSE 464 : 0.0542741 

nnet 464 : -0.4213917 
nnet mean 464 : -0.4302531 
nnet RMSE 464 : 0.1508940 


s: 465 
logit 465 : -0.3420077 
logit mean 465 : -0.4253162 
logit RMSE 465 : 0.06809674 

boosting 465 : -0.4181437 
boosting mean 465 : -0.5048702 
boosting RMSE 465 : 0.1617110 

forest 465 : -0.4240041 
forest mean 465 : -0.3798400 
forest RMSE 465 : 0.05422713 

nnet 465 : -0.420748 
nnet mean 465 : -0.4302327 
nnet RMSE 465 : 0.1507347 


s: 466 
logit 466 : -0.4053463 
logit mean 466 : -0.4252733 
logit RMSE 466 : 0.06802408 

boosting 466 : -0.5668211 
boosting mean 466 : -0.5050032 
boosting RMSE 466 : 0.1617222 

forest 466 : -0.3704451 
forest mean 466 : -0.3798198 
forest RMSE 466 : 0.05418622 

nnet 466 : -0.4957635 
nnet mean 466 : -0.4303733 
nnet RMSE 466 : 0.1506382 


s: 467 
logit 467 : -0.326738 
logit mean 467 : -0.4250623 
logit RMSE 467 : 0.06803573 

boosting 467 : -0.5160775 
boosting mean 467 : -0.5050269 
boosting RMSE 467 : 0.1616382 

forest 467 : -0.3529089 
forest mean 467 : -0.3797622 
forest RMSE 467 : 0.05417202 

nnet 467 : -0.45417 
nnet mean 467 : -0.4304242 
nnet RMSE 467 : 0.1504977 


s: 468 
logit 468 : -0.3847409 
logit mean 468 : -0.4249762 
logit RMSE 468 : 0.06796666 

boosting 468 : -0.545853 
boosting mean 468 : -0.5051141 
boosting RMSE 468 : 0.1616061 

forest 468 : -0.4026144 
forest mean 468 : -0.379811 
forest RMSE 468 : 0.05411425 

nnet 468 : -0.2386778 
nnet mean 468 : -0.4300145 
nnet RMSE 468 : 0.1505217 


s: 469 
logit 469 : -0.5182541 
logit mean 469 : -0.4251750 
logit RMSE 469 : 0.0681134 

boosting 469 : -0.5793993 
boosting mean 469 : -0.5052725 
boosting RMSE 469 : 0.1616461 

forest 469 : -0.4392217 
forest mean 469 : -0.3799377 
forest RMSE 469 : 0.05408686 

nnet 469 : -0.5110736 
nnet mean 469 : -0.4301874 
nnet RMSE 469 : 0.1504486 


s: 470 
logit 470 : -0.4749943 
logit mean 470 : -0.425281 
logit RMSE 470 : 0.06812877 

boosting 470 : -0.5485812 
boosting mean 470 : -0.5053647 
boosting RMSE 470 : 0.1616195 

forest 470 : -0.3719422 
forest mean 470 : -0.3799207 
forest RMSE 470 : 0.05404478 

nnet 470 : -0.6631721 
nnet mean 470 : -0.4306831 
nnet RMSE 470 : 0.1507779 


s: 471 
logit 471 : -0.4839981 
logit mean 471 : -0.4254057 
logit RMSE 471 : 0.06816638 

boosting 471 : -0.1784985 
boosting mean 471 : -0.5046707 
boosting RMSE 471 : 0.1617701 

forest 471 : -0.3937971 
forest mean 471 : -0.3799501 
forest RMSE 471 : 0.05398814 

nnet 471 : -0.3321495 
nnet mean 471 : -0.4304739 
nnet RMSE 471 : 0.1506502 


s: 472 
logit 472 : -0.4633412 
logit mean 472 : -0.4254861 
logit RMSE 472 : 0.06815652 

boosting 472 : -0.582564 
boosting mean 472 : -0.5048357 
boosting RMSE 472 : 0.1618170 

forest 472 : -0.3334961 
forest mean 472 : -0.3798517 
forest RMSE 472 : 0.05401772 

nnet 472 : -0.4476488 
nnet mean 472 : -0.4305103 
nnet RMSE 472 : 0.1505065 


s: 473 
logit 473 : -0.4035621 
logit mean 473 : -0.4254397 
logit RMSE 473 : 0.06808463 

boosting 473 : -0.4114248 
boosting mean 473 : -0.5046382 
boosting RMSE 473 : 0.1616467 

forest 473 : -0.3612818 
forest mean 473 : -0.3798124 
forest RMSE 473 : 0.05398995 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Warning in MatchLoopCfast(N = s1$N, xvars = Kx, All = s1$All, M = s1$M,  :
  Increasing memory because of ties.  I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.
Warning in MatchLoopCfast(N = s1$N, xvars = Kx, All = s1$All, M = s1$M,  :
  Increasing memory because of ties.  I would be faster with the ties=FALSE option.

nnet 473 : -0.1129073 
nnet mean 473 : -0.4298388 
nnet RMSE 473 : 0.1509257 


s: 474 
logit 474 : -0.4202033 
logit mean 474 : -0.4254287 
logit RMSE 474 : 0.0680191 

boosting 474 : -0.4864739 
boosting mean 474 : -0.5045999 
boosting RMSE 474 : 0.1615249 

forest 474 : -0.3244332 
forest mean 474 : -0.3796956 
forest RMSE 474 : 0.05404454 

nnet 474 : -0.2751207 
nnet mean 474 : -0.4295124 
nnet RMSE 474 : 0.1508755 


s: 475 
logit 475 : -0.4485426 
logit mean 475 : -0.4254773 
logit RMSE 475 : 0.06798396 

boosting 475 : -0.749119 
boosting mean 475 : -0.5051147 
boosting RMSE 475 : 0.162148 

forest 475 : -0.4134421 
forest mean 475 : -0.3797667 
forest RMSE 475 : 0.05399114 

nnet 475 : -0.5568121 
nnet mean 475 : -0.4297804 
nnet RMSE 475 : 0.1508883 


s: 476 
logit 476 : -0.3715443 
logit mean 476 : -0.425364 
logit RMSE 476 : 0.06792503 

boosting 476 : -0.4082653 
boosting mean 476 : -0.5049112 
boosting RMSE 476 : 0.161978 

forest 476 : -0.3693806 
forest mean 476 : -0.3797448 
forest RMSE 476 : 0.05395265 

nnet 476 : -0.6134224 
nnet mean 476 : -0.4301662 
nnet RMSE 476 : 0.1510468 


s: 477 
logit 477 : -0.4977089 
logit mean 477 : -0.4255157 
logit RMSE 477 : 0.06800112 

boosting 477 : -0.5519675 
boosting mean 477 : -0.5050099 
boosting RMSE 477 : 0.1619577 

forest 477 : -0.3527826 
forest mean 477 : -0.3796883 
forest RMSE 477 : 0.05393941 

nnet 477 : -0.0809307 
nnet mean 477 : -0.429434 
nnet RMSE 477 : 0.1515939 


s: 478 
logit 478 : -0.3447880 
logit mean 478 : -0.4253468 
logit RMSE 478 : 0.06797688 

boosting 478 : -0.5185209 
boosting mean 478 : -0.5050381 
boosting RMSE 478 : 0.1618790 

forest 478 : -0.4143984 
forest mean 478 : -0.3797609 
forest RMSE 478 : 0.05388699 

nnet 478 : -0.1988223 
nnet mean 478 : -0.4289516 
nnet RMSE 478 : 0.1517146 


s: 479 
logit 479 : -0.4406359 
logit mean 479 : -0.4253787 
logit RMSE 479 : 0.06793126 

boosting 479 : -0.5664997 
boosting mean 479 : -0.5051664 
boosting RMSE 479 : 0.1618888 

forest 479 : -0.3942616 
forest mean 479 : -0.3797912 
forest RMSE 479 : 0.05383135 

nnet 479 : -0.3994896 
nnet mean 479 : -0.4288901 
nnet RMSE 479 : 0.1515562 


s: 480 
logit 480 : -0.4415315 
logit mean 480 : -0.4254124 
logit RMSE 480 : 0.06788693 

boosting 480 : -0.4913049 
boosting mean 480 : -0.5051376 
boosting RMSE 480 : 0.1617737 

forest 480 : -0.5142636 
forest mean 480 : -0.3800714 
forest RMSE 480 : 0.05402756 

nnet 480 : -0.1938713 
nnet mean 480 : -0.4284005 
nnet RMSE 480 : 0.1516903 


s: 481 
logit 481 : -0.4125492 
logit mean 481 : -0.4253856 
logit RMSE 481 : 0.06781874 

boosting 481 : -0.7444367 
boosting mean 481 : -0.5056351 
boosting RMSE 481 : 0.1623668 

forest 481 : -0.3850029 
forest mean 481 : -0.3800816 
forest RMSE 481 : 0.0539757 

nnet 481 : -0.05937705 
nnet mean 481 : -0.4276333 
nnet RMSE 481 : 0.1523263 


s: 482 
logit 482 : -0.3684689 
logit mean 482 : -0.4252676 
logit RMSE 482 : 0.06776358 

boosting 482 : -0.2889843 
boosting mean 482 : -0.5051856 
boosting RMSE 482 : 0.1622771 

forest 482 : -0.3747387 
forest mean 482 : -0.3800705 
forest RMSE 482 : 0.05393195 

nnet 482 : -0.4114612 
nnet mean 482 : -0.4275997 
nnet RMSE 482 : 0.1521691 


s: 483 
logit 483 : -0.5061992 
logit mean 483 : -0.4254351 
logit RMSE 483 : 0.06786564 

boosting 483 : -0.6556804 
boosting mean 483 : -0.5054972 
boosting RMSE 483 : 0.1625259 

forest 483 : -0.4500047 
forest mean 483 : -0.3802153 
forest RMSE 483 : 0.05392412 

nnet 483 : -0.5760333 
nnet mean 483 : -0.427907 
nnet RMSE 483 : 0.1522224 


s: 484 
logit 484 : -0.4589024 
logit mean 484 : -0.4255043 
logit RMSE 484 : 0.06784835 

boosting 484 : -0.7428978 
boosting mean 484 : -0.5059877 
boosting RMSE 484 : 0.1631044 

forest 484 : -0.414049 
forest mean 484 : -0.3802852 
forest RMSE 484 : 0.05387217 

nnet 484 : -0.4795898 
nnet mean 484 : -0.4280138 
nnet RMSE 484 : 0.1521081 


s: 485 
logit 485 : -0.320604 
logit mean 485 : -0.425288 
logit RMSE 485 : 0.06787418 

boosting 485 : -0.4175778 
boosting mean 485 : -0.5058054 
boosting RMSE 485 : 0.1629381 

forest 485 : -0.3444816 
forest mean 485 : -0.3802114 
forest RMSE 485 : 0.05387561 

nnet 485 : -0.1913759 
nnet mean 485 : -0.4275259 
nnet RMSE 485 : 0.1522462 


s: 486 
logit 486 : -0.3923631 
logit mean 486 : -0.4252202 
logit RMSE 486 : 0.0678052 

boosting 486 : -0.573901 
boosting mean 486 : -0.5059455 
boosting RMSE 486 : 0.1629614 

forest 486 : -0.5070989 
forest mean 486 : -0.3804725 
forest RMSE 486 : 0.05403897 

nnet 486 : -0.4488347 
nnet mean 486 : -0.4275697 
nnet RMSE 486 : 0.1521056 


s: 487 
logit 487 : -0.3272624 
logit mean 487 : -0.4250191 
logit RMSE 487 : 0.06781569 

boosting 487 : -0.3515728 
boosting mean 487 : -0.5056285 
boosting RMSE 487 : 0.1628088 

forest 487 : -0.4103584 
forest mean 487 : -0.3805338 
forest RMSE 487 : 0.0539855 

nnet 487 : -0.2800205 
nnet mean 487 : -0.4272668 
nnet RMSE 487 : 0.1520466 


s: 488 
logit 488 : -0.3485254 
logit mean 488 : -0.4248623 
logit RMSE 488 : 0.06778623 

boosting 488 : -0.6407957 
boosting mean 488 : -0.5059055 
boosting RMSE 488 : 0.1630067 

forest 488 : -0.4892083 
forest mean 488 : -0.3807565 
forest RMSE 488 : 0.05408114 

nnet 488 : -0.3710795 
nnet mean 488 : -0.4271516 
nnet RMSE 488 : 0.1518964 


s: 489 
logit 489 : -0.4288967 
logit mean 489 : -0.4248706 
logit RMSE 489 : 0.0677295 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 489 : -0.4724635 
boosting mean 489 : -0.5058371 
boosting RMSE 489 : 0.1628729 

forest 489 : -0.4103337 
forest mean 489 : -0.380817 
forest RMSE 489 : 0.05402784 

nnet 489 : -0.572203 
nnet mean 489 : -0.4274483 
nnet RMSE 489 : 0.1519407 


s: 490 
logit 490 : -0.4334457 
logit mean 490 : -0.4248881 
logit RMSE 490 : 0.06767722 

boosting 490 : -0.5606 
boosting mean 490 : -0.5059489 
boosting RMSE 490 : 0.1628683 

forest 490 : -0.4038501 
forest mean 490 : -0.380864 
forest RMSE 490 : 0.05397296 

nnet 490 : -0.3403417 
nnet mean 490 : -0.4272705 
nnet RMSE 490 : 0.1518095 


s: 491 
logit 491 : -0.4727623 
logit mean 491 : -0.4249856 
logit RMSE 491 : 0.06768796 

boosting 491 : -0.4842502 
boosting mean 491 : -0.5059047 
boosting RMSE 491 : 0.1627468 

forest 491 : -0.4230935 
forest mean 491 : -0.38095 
forest RMSE 491 : 0.05392804 

nnet 491 : -0.4831238 
nnet mean 491 : -0.4273842 
nnet RMSE 491 : 0.1517012 


s: 492 
logit 492 : -0.3742415 
logit mean 492 : -0.4248825 
logit RMSE 492 : 0.06762911 

boosting 492 : -0.5368206 
boosting mean 492 : -0.5059675 
boosting RMSE 492 : 0.1626983 

forest 492 : -0.4943851 
forest mean 492 : -0.3811806 
forest RMSE 492 : 0.054041 

nnet 492 : -0.3248255 
nnet mean 492 : -0.4271758 
nnet RMSE 492 : 0.1515848 


s: 493 
logit 493 : -0.3917646 
logit mean 493 : -0.4248153 
logit RMSE 493 : 0.0675615 

boosting 493 : -0.5908565 
boosting mean 493 : -0.5061397 
boosting RMSE 493 : 0.1627604 

forest 493 : -0.3609007 
forest mean 493 : -0.3811395 
forest RMSE 493 : 0.05401487 

nnet 493 : -0.4026941 
nnet mean 493 : -0.4271261 
nnet RMSE 493 : 0.1514311 


s: 494 
logit 494 : -0.5356047 
logit mean 494 : -0.4250395 
logit RMSE 494 : 0.06776829 

boosting 494 : -0.3639798 
boosting mean 494 : -0.5058519 
boosting RMSE 494 : 0.1626036 

forest 494 : -0.3490056 
forest mean 494 : -0.3810744 
forest RMSE 494 : 0.05400893 

nnet 494 : -0.3614034 
nnet mean 494 : -0.4269931 
nnet RMSE 494 : 0.1512877 


s: 495 
logit 495 : -0.3882589 
logit mean 495 : -0.4249652 
logit RMSE 495 : 0.06770185 

boosting 495 : -0.5839806 
boosting mean 495 : -0.5060098 
boosting RMSE 495 : 0.1626496 

forest 495 : -0.4569901 
forest mean 495 : -0.3812278 
forest RMSE 495 : 0.05401512 

nnet 495 : -0.3032323 
nnet mean 495 : -0.4267431 
nnet RMSE 495 : 0.1511974 


s: 496 
logit 496 : -0.3937001 
logit mean 496 : -0.4249022 
logit RMSE 496 : 0.06763416 

boosting 496 : -0.4337704 
boosting mean 496 : -0.5058641 
boosting RMSE 496 : 0.1624927 

forest 496 : -0.4113286 
forest mean 496 : -0.3812885 
forest RMSE 496 : 0.05396304 

nnet 496 : -0.6042232 
nnet mean 496 : -0.4271009 
nnet RMSE 496 : 0.1513230 


s: 497 
logit 497 : -0.4609116 
logit mean 497 : -0.4249747 
logit RMSE 497 : 0.06762131 

boosting 497 : -0.4383180 
boosting mean 497 : -0.5057282 
boosting RMSE 497 : 0.1623382 

forest 497 : -0.4437575 
forest mean 497 : -0.3814142 
forest RMSE 497 : 0.05394444 

nnet 497 : -0.451601 
nnet mean 497 : -0.4271502 
nnet RMSE 497 : 0.1511884 


s: 498 
logit 498 : -0.4335772 
logit mean 498 : -0.4249919 
logit RMSE 498 : 0.06757014 

boosting 498 : -0.5470289 
boosting mean 498 : -0.5058111 
boosting RMSE 498 : 0.1623089 

forest 498 : -0.3544258 
forest mean 498 : -0.38136 
forest RMSE 498 : 0.05392893 

nnet 498 : -0.3489608 
nnet mean 498 : -0.4269932 
nnet RMSE 498 : 0.1510538 


s: 499 
logit 499 : -0.4258386 
logit mean 499 : -0.4249936 
logit RMSE 499 : 0.0675123 

boosting 499 : -0.5991176 
boosting mean 499 : -0.5059981 
boosting RMSE 499 : 0.1623910 

forest 499 : -0.4482931 
forest mean 499 : -0.3814941 
forest RMSE 499 : 0.05391823 

nnet 499 : -0.3786101 
nnet mean 499 : -0.4268962 
nnet RMSE 499 : 0.1509054 


s: 500 
logit 500 : -0.5090438 
logit mean 500 : -0.4251617 
logit RMSE 500 : 0.06762083 

boosting 500 : -0.5438004 
boosting mean 500 : -0.5060737 
boosting RMSE 500 : 0.1623560 

forest 500 : -0.4703113 
forest mean 500 : -0.3816717 
forest RMSE 500 : 0.05395599 

nnet 500 : -0.5909933 
nnet mean 500 : -0.4272244 
nnet RMSE 500 : 0.1509962 


s: 501 
logit 501 : -0.503467 
logit mean 501 : -0.425318 
logit RMSE 501 : 0.06771128 

boosting 501 : -0.4746701 
boosting mean 501 : -0.506011 
boosting RMSE 501 : 0.1622282 

forest 501 : -0.3041862 
forest mean 501 : -0.3815171 
forest RMSE 501 : 0.05407182 

nnet 501 : -0.5704483 
nnet mean 501 : -0.4275103 
nnet RMSE 501 : 0.1510376 


s: 502 
logit 502 : -0.4583585 
logit mean 502 : -0.4253838 
logit RMSE 502 : 0.06769394 

boosting 502 : -0.5714894 
boosting mean 502 : -0.5061415 
boosting RMSE 502 : 0.1622471 

forest 502 : -0.4232484 
forest mean 502 : -0.3816002 
forest RMSE 502 : 0.0540279 

nnet 502 : -0.421878 
nnet mean 502 : -0.4274991 
nnet RMSE 502 : 0.1508902 


s: 503 
logit 503 : -0.3839943 
logit mean 503 : -0.4253016 
logit RMSE 503 : 0.06763038 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 503 : -0.5690551 
boosting mean 503 : -0.5062666 
boosting RMSE 503 : 0.1622610 

forest 503 : -0.3451725 
forest mean 503 : -0.3815278 
forest RMSE 503 : 0.0540295 

nnet 503 : -0.3528452 
nnet mean 503 : -0.4273506 
nnet RMSE 503 : 0.1507548 


s: 504 
logit 504 : -0.4712699 
logit mean 504 : -0.4253928 
logit RMSE 504 : 0.0676378 

boosting 504 : -0.545033 
boosting mean 504 : -0.5063435 
boosting RMSE 504 : 0.1622286 

forest 504 : -0.4067348 
forest mean 504 : -0.3815778 
forest RMSE 504 : 0.05397671 

nnet 504 : -0.5007144 
nnet mean 504 : -0.4274962 
nnet RMSE 504 : 0.1506720 


s: 505 
logit 505 : -0.4668464 
logit mean 505 : -0.4254749 
logit RMSE 505 : 0.06763624 

boosting 505 : -0.6046536 
boosting mean 505 : -0.5065382 
boosting RMSE 505 : 0.1623236 

forest 505 : -0.450477 
forest mean 505 : -0.3817142 
forest RMSE 505 : 0.05397 

nnet 505 : -0.4272366 
nnet mean 505 : -0.4274957 
nnet RMSE 505 : 0.1505276 


s: 506 
logit 506 : -0.449435 
logit mean 506 : -0.4255222 
logit RMSE 506 : 0.0676051 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 506 : -0.5795305 
boosting mean 506 : -0.5066824 
boosting RMSE 506 : 0.1623594 

forest 506 : -0.3597226 
forest mean 506 : -0.3816708 
forest RMSE 506 : 0.05394637 

nnet 506 : -0.6079762 
nnet mean 506 : -0.4278524 
nnet RMSE 506 : 0.1506627 


s: 507 
logit 507 : -0.4055871 
logit mean 507 : -0.4254829 
logit RMSE 507 : 0.06753885 

boosting 507 : -0.5981823 
boosting mean 507 : -0.5068629 
boosting RMSE 507 : 0.1624378 

forest 507 : -0.4515635 
forest mean 507 : -0.3818086 
forest RMSE 507 : 0.05394177 

nnet 507 : -0.4268056 
nnet mean 507 : -0.4278503 
nnet RMSE 507 : 0.1505188 


s: 508 
logit 508 : -0.3673520 
logit mean 508 : -0.4253685 
logit RMSE 508 : 0.06748789 

boosting 508 : -0.4846801 
boosting mean 508 : -0.5068192 
boosting RMSE 508 : 0.1623213 

forest 508 : -0.3718865 
forest mean 508 : -0.3817891 
forest RMSE 508 : 0.05390309 

nnet 508 : -0.4370147 
nnet mean 508 : -0.4278684 
nnet RMSE 508 : 0.1503795 


s: 509 
logit 509 : -0.4204504 
logit mean 509 : -0.4253588 
logit RMSE 509 : 0.06742765 

boosting 509 : -0.7751952 
boosting mean 509 : -0.5073465 
boosting RMSE 509 : 0.1630123 

forest 509 : -0.3319435 
forest mean 509 : -0.3816912 
forest RMSE 509 : 0.05393454 

nnet 509 : -0.923494 
nnet mean 509 : -0.4288421 
nnet RMSE 509 : 0.1520131 


s: 510 
logit 510 : -0.617591 
logit mean 510 : -0.4257357 
logit RMSE 510 : 0.06804711 

boosting 510 : -0.3964873 
boosting mean 510 : -0.5071291 
boosting RMSE 510 : 0.1628525 

forest 510 : -0.4470852 
forest mean 510 : -0.3818194 
forest RMSE 510 : 0.05392196 

nnet 510 : -0.2828407 
nnet mean 510 : -0.4285558 
nnet RMSE 510 : 0.1519526 


s: 511 
logit 511 : -0.3740260 
logit mean 511 : -0.4256345 
logit RMSE 511 : 0.0679902 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 511 : -0.504858 
boosting mean 511 : -0.5071247 
boosting RMSE 511 : 0.1627592 

forest 511 : -0.3134429 
forest mean 511 : -0.3816856 
forest RMSE 511 : 0.05400508 

nnet 511 : -0.5216461 
nnet mean 511 : -0.428738 
nnet RMSE 511 : 0.1518992 


s: 512 
logit 512 : -0.4031656 
logit mean 512 : -0.4255906 
logit RMSE 512 : 0.06792392 

boosting 512 : -0.5685981 
boosting mean 512 : -0.5072447 
boosting RMSE 512 : 0.1627708 

forest 512 : -0.3384417 
forest mean 512 : -0.3816011 
forest RMSE 512 : 0.05402087 

nnet 512 : -0.4568224 
nnet mean 512 : -0.4287928 
nnet RMSE 512 : 0.1517715 


s: 513 
logit 513 : -0.4673703 
logit mean 513 : -0.4256721 
logit RMSE 513 : 0.06792284 

boosting 513 : -0.4476644 
boosting mean 513 : -0.5071286 
boosting RMSE 513 : 0.1626257 

forest 513 : -0.2824690 
forest mean 513 : -0.3814079 
forest RMSE 513 : 0.05421709 

nnet 513 : -0.5846751 
nnet mean 513 : -0.4290967 
nnet RMSE 513 : 0.1518426 


s: 514 
logit 514 : -0.4901352 
logit mean 514 : -0.4257975 
logit RMSE 514 : 0.0679731 

boosting 514 : -0.4832426 
boosting mean 514 : -0.5070821 
boosting RMSE 514 : 0.1625089 

forest 514 : -0.3924532 
forest mean 514 : -0.3814294 
forest RMSE 514 : 0.05416534 

nnet 514 : -0.4816898 
nnet mean 514 : -0.429199 
nnet RMSE 514 : 0.1517376 


s: 515 
logit 515 : -0.4394356 
logit mean 515 : -0.425824 
logit RMSE 515 : 0.06792931 

boosting 515 : -0.4135719 
boosting mean 515 : -0.5069005 
boosting RMSE 515 : 0.1623521 

forest 515 : -0.3250177 
forest mean 515 : -0.3813198 
forest RMSE 515 : 0.05421351 

nnet 515 : -0.5394506 
nnet mean 515 : -0.4294131 
nnet RMSE 515 : 0.1517147 


s: 516 
logit 516 : -0.283343 
logit mean 516 : -0.4255479 
logit RMSE 516 : 0.0680575 

boosting 516 : -0.3508707 
boosting mean 516 : -0.5065982 
boosting RMSE 516 : 0.1622092 

forest 516 : -0.4067277 
forest mean 516 : -0.3813691 
forest RMSE 516 : 0.05416176 

nnet 516 : -0.2472853 
nnet mean 516 : -0.4290601 
nnet RMSE 516 : 0.1517167 


s: 517 
logit 517 : -0.3623666 
logit mean 517 : -0.4254256 
logit RMSE 517 : 0.06801178 

boosting 517 : -0.611244 
boosting mean 517 : -0.5068006 
boosting RMSE 517 : 0.1623183 

forest 517 : -0.3845484 
forest mean 517 : -0.3813752 
forest RMSE 517 : 0.05411362 

nnet 517 : -0.4452589 
nnet mean 517 : -0.4290915 
nnet RMSE 517 : 0.1515829 


s: 518 
logit 518 : -0.4459981 
logit mean 518 : -0.4254654 
logit RMSE 518 : 0.06797615 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 518 : -0.5339015 
boosting mean 518 : -0.5068529 
boosting RMSE 518 : 0.1622682 

forest 518 : -0.3807483 
forest mean 518 : -0.381374 
forest RMSE 518 : 0.05406798 

nnet 518 : -0.4153044 
nnet mean 518 : -0.4290648 
nnet RMSE 518 : 0.1514380 


s: 519 
logit 519 : -0.4354335 
logit mean 519 : -0.4254846 
logit RMSE 519 : 0.06792844 

boosting 519 : -0.4240959 
boosting mean 519 : -0.5066934 
boosting RMSE 519 : 0.1621153 

forest 519 : -0.4371506 
forest mean 519 : -0.3814815 
forest RMSE 519 : 0.05404048 

nnet 519 : -0.3355739 
nnet mean 519 : -0.4288847 
nnet RMSE 519 : 0.1513185 


s: 520 
logit 520 : -0.4523046 
logit mean 520 : -0.4255361 
logit RMSE 520 : 0.06790185 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 520 : -0.4319895 
boosting mean 520 : -0.5065498 
boosting RMSE 520 : 0.1619654 

forest 520 : -0.4205907 
forest mean 520 : -0.3815567 
forest RMSE 520 : 0.05399604 

nnet 520 : -0.3717999 
nnet mean 520 : -0.4287749 
nnet RMSE 520 : 0.151178 


s: 521 
logit 521 : -0.3908428 
logit mean 521 : -0.4254696 
logit RMSE 521 : 0.06783784 

boosting 521 : -0.3487604 
boosting mean 521 : -0.5062469 
boosting RMSE 521 : 0.1618255 

forest 521 : -0.3319705 
forest mean 521 : -0.3814615 
forest RMSE 521 : 0.05402647 

nnet 521 : -0.4596619 
nnet mean 521 : -0.4288342 
nnet RMSE 521 : 0.1510555 


s: 522 
logit 522 : -0.4944849 
logit mean 522 : -0.4256018 
logit RMSE 522 : 0.06789889 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 522 : -0.5785809 
boosting mean 522 : -0.5063855 
boosting RMSE 522 : 0.1618592 

forest 522 : -0.3981575 
forest mean 522 : -0.3814935 
forest RMSE 522 : 0.05397475 

nnet 522 : -0.591802 
nnet mean 522 : -0.4291464 
nnet RMSE 522 : 0.151144 


s: 523 
logit 523 : -0.4482447 
logit mean 523 : -0.4256451 
logit RMSE 523 : 0.06786674 

boosting 523 : -0.4099553 
boosting mean 523 : -0.5062011 
boosting RMSE 523 : 0.161705 

forest 523 : -0.3449948 
forest mean 523 : -0.3814237 
forest RMSE 523 : 0.05397674 

nnet 523 : -0.07458932 
nnet mean 523 : -0.4284685 
nnet RMSE 523 : 0.1516684 


s: 524 
logit 524 : -0.3931584 
logit mean 524 : -0.4255831 
logit RMSE 524 : 0.0678026 

boosting 524 : -0.3698849 
boosting mean 524 : -0.505941 
boosting RMSE 524 : 0.1615560 

forest 524 : -0.4503743 
forest mean 524 : -0.3815553 
forest RMSE 524 : 0.0539701 

nnet 524 : -0.6590988 
nnet mean 524 : -0.4289086 
nnet RMSE 524 : 0.1519458 


s: 525 
logit 525 : -0.5514299 
logit mean 525 : -0.4258228 
logit RMSE 525 : 0.06805964 

boosting 525 : -0.5855455 
boosting mean 525 : -0.5060926 
boosting RMSE 525 : 0.1616051 

forest 525 : -0.444926 
forest mean 525 : -0.381676 
forest RMSE 525 : 0.05395431 

nnet 525 : -0.6034579 
nnet mean 525 : -0.4292411 
nnet RMSE 525 : 0.1520605 


s: 526 
logit 526 : -0.4163441 
logit mean 526 : -0.4258048 
logit RMSE 526 : 0.06799865 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 526 : -0.4993089 
boosting mean 526 : -0.5060797 
boosting RMSE 526 : 0.1615094 

forest 526 : -0.4760595 
forest mean 526 : -0.3818554 
forest RMSE 526 : 0.05400492 

nnet 526 : -0.4901043 
nnet mean 526 : -0.4293568 
nnet RMSE 526 : 0.1519667 


s: 527 
logit 527 : -0.2658211 
logit mean 527 : -0.4255012 
logit RMSE 527 : 0.06818508 

boosting 527 : -0.4433378 
boosting mean 527 : -0.5059606 
boosting RMSE 527 : 0.1613672 

forest 527 : -0.2920488 
forest mean 527 : -0.381685 
forest RMSE 527 : 0.0541582 

nnet 527 : -0.3804608 
nnet mean 527 : -0.429264 
nnet RMSE 527 : 0.1518248 


s: 528 
logit 528 : -0.3772444 
logit mean 528 : -0.4254098 
logit RMSE 528 : 0.06812768 

boosting 528 : -0.4705289 
boosting mean 528 : -0.5058935 
boosting RMSE 528 : 0.1612435 

forest 528 : -0.3351763 
forest mean 528 : -0.3815969 
forest RMSE 528 : 0.05418038 

nnet 528 : -0.3915148 
nnet mean 528 : -0.4291925 
nnet RMSE 528 : 0.1516814 


s: 529 
logit 529 : -0.4459173 
logit mean 529 : -0.4254486 
logit RMSE 529 : 0.06809253 

boosting 529 : -0.5042442 
boosting mean 529 : -0.5058904 
boosting RMSE 529 : 0.1611548 

forest 529 : -0.4500097 
forest mean 529 : -0.3817263 
forest RMSE 529 : 0.0541728 

nnet 529 : -0.3701937 
nnet mean 529 : -0.429081 
nnet RMSE 529 : 0.1515435 


s: 530 
logit 530 : -0.3625544 
logit mean 530 : -0.4253299 
logit RMSE 530 : 0.0680477 

boosting 530 : -0.4712176 
boosting mean 530 : -0.505825 
boosting RMSE 530 : 0.1610324 

forest 530 : -0.3841206 
forest mean 530 : -0.3817308 
forest RMSE 530 : 0.05412606 

nnet 530 : -0.4795875 
nnet mean 530 : -0.4291763 
nnet RMSE 530 : 0.1514399 


s: 531 
logit 531 : -0.4318081 
logit mean 531 : -0.4253421 
logit RMSE 531 : 0.06799761 

boosting 531 : -0.5315292 
boosting mean 531 : -0.5058734 
boosting RMSE 531 : 0.1609819 

forest 531 : -0.3883115 
forest mean 531 : -0.3817432 
forest RMSE 531 : 0.05407745 

nnet 531 : -0.7177237 
nnet mean 531 : -0.4297197 
nnet RMSE 531 : 0.1519242 


s: 532 
logit 532 : -0.4260499 
logit mean 532 : -0.4253434 
logit RMSE 532 : 0.06794306 

boosting 532 : -0.5678632 
boosting mean 532 : -0.5059899 
boosting RMSE 532 : 0.1609951 

forest 532 : -0.4759065 
forest mean 532 : -0.3819202 
forest RMSE 532 : 0.05412674 

nnet 532 : -0.5407292 
nnet mean 532 : -0.4299284 
nnet RMSE 532 : 0.1519040 


s: 533 
logit 533 : -0.3795843 
logit mean 533 : -0.4252576 
logit RMSE 533 : 0.06788506 

boosting 533 : -0.4345257 
boosting mean 533 : -0.5058558 
boosting RMSE 533 : 0.1608510 

forest 533 : -0.3709652 
forest mean 533 : -0.3818996 
forest RMSE 533 : 0.05409057 

nnet 533 : -0.3962873 
nnet mean 533 : -0.4298652 
nnet RMSE 533 : 0.1517615 


s: 534 
logit 534 : -0.4473802 
logit mean 534 : -0.425299 
logit RMSE 534 : 0.06785245 

boosting 534 : -0.6278018 
boosting mean 534 : -0.5060842 
boosting RMSE 534 : 0.1610024 

forest 534 : -0.3099906 
forest mean 534 : -0.3817650 
forest RMSE 534 : 0.05418009 

nnet 534 : -0.4132769 
nnet mean 534 : -0.4298342 
nnet RMSE 534 : 0.1516204 


s: 535 
logit 535 : -0.4393483 
logit mean 535 : -0.4253252 
logit RMSE 535 : 0.06781035 

boosting 535 : -0.504262 
boosting mean 535 : -0.5060808 
boosting RMSE 535 : 0.1609150 

forest 535 : -0.3856015 
forest mean 535 : -0.3817721 
forest RMSE 535 : 0.05413301 

nnet 535 : -0.547528 
nnet mean 535 : -0.4300542 
nnet RMSE 535 : 0.1516129 


s: 536 
logit 536 : -0.3908116 
logit mean 536 : -0.4252609 
logit RMSE 536 : 0.06774823 

boosting 536 : -0.5658483 
boosting mean 536 : -0.5061923 
boosting RMSE 536 : 0.1609243 

forest 536 : -0.3900201 
forest mean 536 : -0.3817875 
forest RMSE 536 : 0.05408421 

nnet 536 : -0.5109298 
nnet mean 536 : -0.4302051 
nnet RMSE 536 : 0.1515471 


s: 537 
logit 537 : -0.3921087 
logit mean 537 : -0.4251991 
logit RMSE 537 : 0.06768597 

boosting 537 : -0.3216127 
boosting mean 537 : -0.5058486 
boosting RMSE 537 : 0.1608100 

forest 537 : -0.3548537 
forest mean 537 : -0.3817374 
forest RMSE 537 : 0.05406894 

nnet 537 : -0.1659830 
nnet mean 537 : -0.429713 
nnet RMSE 537 : 0.1517424 


s: 538 
logit 538 : -0.3806367 
logit mean 538 : -0.4251163 
logit RMSE 538 : 0.06762819 

boosting 538 : -0.3957408 
boosting mean 538 : -0.5056439 
boosting RMSE 538 : 0.1606606 

forest 538 : -0.3539708 
forest mean 538 : -0.3816858 
forest RMSE 538 : 0.0540551 

nnet 538 : -0.1976493 
nnet mean 538 : -0.4292817 
nnet RMSE 538 : 0.1518521 


s: 539 
logit 539 : -0.5348562 
logit mean 539 : -0.4253199 
logit RMSE 539 : 0.06781466 

boosting 539 : -0.517853 
boosting mean 539 : -0.5056666 
boosting RMSE 539 : 0.1605917 

forest 539 : -0.4469452 
forest mean 539 : -0.3818068 
forest RMSE 539 : 0.05404278 

nnet 539 : -0.6491375 
nnet mean 539 : -0.4296896 
nnet RMSE 539 : 0.1520902 


s: 540 
logit 540 : -0.3695579 
logit mean 540 : -0.4252166 
logit RMSE 540 : 0.0677645 

boosting 540 : -0.6014718 
boosting mean 540 : -0.505844 
boosting RMSE 540 : 0.1606770 

forest 540 : -0.3452465 
forest mean 540 : -0.3817391 
forest RMSE 540 : 0.0540441 

nnet 540 : -0.3963245 
nnet mean 540 : -0.4296278 
nnet RMSE 540 : 0.1519494 


s: 541 
logit 541 : -0.3169142 
logit mean 541 : -0.4250164 
logit RMSE 541 : 0.06779601 

boosting 541 : -0.2907712 
boosting mean 541 : -0.5054464 
boosting RMSE 541 : 0.1605971 

forest 541 : -0.3217026 
forest mean 541 : -0.3816281 
forest RMSE 541 : 0.05409896 

nnet 541 : -0.5676315 
nnet mean 541 : -0.4298829 
nnet RMSE 541 : 0.1519799 


s: 542 
logit 542 : -0.3458238 
logit mean 542 : -0.4248703 
logit RMSE 542 : 0.0677734 

boosting 542 : -0.2215513 
boosting mean 542 : -0.5049226 
boosting RMSE 542 : 0.1606319 

forest 542 : -0.3637009 
forest mean 542 : -0.3815951 
forest RMSE 542 : 0.05407152 

nnet 542 : -0.5944558 
nnet mean 542 : -0.4301865 
nnet RMSE 542 : 0.1520692 


s: 543 
logit 543 : -0.5241156 
logit mean 543 : -0.4250531 
logit RMSE 543 : 0.06792014 

boosting 543 : -0.4912263 
boosting mean 543 : -0.5048974 
boosting RMSE 543 : 0.1605317 

forest 543 : -0.4178635 
forest mean 543 : -0.3816619 
forest RMSE 543 : 0.05402714 

nnet 543 : -0.4286627 
nnet mean 543 : -0.4301837 
nnet RMSE 543 : 0.1519341 


s: 544 
logit 544 : -0.3314937 
logit mean 544 : -0.4248811 
logit RMSE 544 : 0.06792122 

boosting 544 : -0.6797637 
boosting mean 544 : -0.5052189 
boosting RMSE 544 : 0.1608319 

forest 544 : -0.379913 
forest mean 544 : -0.3816587 
forest RMSE 544 : 0.05398433 

nnet 544 : -0.4650342 
nnet mean 544 : -0.4302478 
nnet RMSE 544 : 0.1518200 


s: 545 
logit 545 : -0.4497077 
logit mean 545 : -0.4249267 
logit RMSE 545 : 0.06789227 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 545 : -0.5205772 
boosting mean 545 : -0.505247 
boosting RMSE 545 : 0.1607673 

forest 545 : -0.2896495 
forest mean 545 : -0.3814898 
forest RMSE 545 : 0.05414152 

nnet 545 : -0.5299473 
nnet mean 545 : -0.4304307 
nnet RMSE 545 : 0.1517827 


s: 546 
logit 546 : -0.3890245 
logit mean 546 : -0.4248609 
logit RMSE 546 : 0.0678317 

boosting 546 : -0.4105053 
boosting mean 546 : -0.5050735 
boosting RMSE 546 : 0.1606207 

forest 546 : -0.3641226 
forest mean 546 : -0.381458 
forest RMSE 546 : 0.05411371 

nnet 546 : -0.2142754 
nnet mean 546 : -0.4300348 
nnet RMSE 546 : 0.1518518 


s: 547 
logit 547 : -0.4248188 
logit mean 547 : -0.4248608 
logit RMSE 547 : 0.06777798 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 547 : -0.3978734 
boosting mean 547 : -0.5048775 
boosting RMSE 547 : 0.1604738 

forest 547 : -0.3948025 
forest mean 547 : -0.3814824 
forest RMSE 547 : 0.05406468 

nnet 547 : -0.4843212 
nnet mean 547 : -0.4301341 
nnet RMSE 547 : 0.1517558 


s: 548 
logit 548 : -0.383914 
logit mean 548 : -0.4247861 
logit RMSE 548 : 0.06771959 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 548 : -0.4301369 
boosting mean 548 : -0.5047412 
boosting RMSE 548 : 0.1603325 

forest 548 : -0.4672382 
forest mean 548 : -0.3816389 
forest RMSE 548 : 0.05409164 

nnet 548 : -0.5486339 
nnet mean 548 : -0.4303503 
nnet RMSE 548 : 0.1517501 


s: 549 
logit 549 : -0.4101956 
logit mean 549 : -0.4247595 
logit RMSE 549 : 0.06765929 

boosting 549 : -0.4128581 
boosting mean 549 : -0.5045738 
boosting RMSE 549 : 0.1601873 

forest 549 : -0.2955362 
forest mean 549 : -0.3814821 
forest RMSE 549 : 0.05422595 

nnet 549 : -0.4810967 
nnet mean 549 : -0.4304427 
nnet RMSE 549 : 0.1516514 


s: 550 
logit 550 : -0.3604195 
logit mean 550 : -0.4246426 
logit RMSE 550 : 0.06761882 

boosting 550 : -0.5517839 
boosting mean 550 : -0.5046596 
boosting RMSE 550 : 0.1601725 

forest 550 : -0.4190508 
forest mean 550 : -0.3815504 
forest RMSE 550 : 0.05418272 

nnet 550 : -0.2992780 
nnet mean 550 : -0.4302043 
nnet RMSE 550 : 0.1515743 


s: 551 
logit 551 : -0.419395 
logit mean 551 : -0.424633 
logit RMSE 551 : 0.06756248 

boosting 551 : -0.5435283 
boosting mean 551 : -0.5047302 
boosting RMSE 551 : 0.1601438 

forest 551 : -0.3538065 
forest mean 551 : -0.3815 
forest RMSE 551 : 0.05416929 

nnet 551 : -0.2411188 
nnet mean 551 : -0.4298611 
nnet RMSE 551 : 0.1515879 


s: 552 
logit 552 : -0.4902277 
logit mean 552 : -0.4247519 
logit RMSE 552 : 0.06761041 

boosting 552 : -0.6153896 
boosting mean 552 : -0.5049306 
boosting RMSE 552 : 0.1602611 

forest 552 : -0.4212153 
forest mean 552 : -0.381572 
forest RMSE 552 : 0.05412773 

nnet 552 : -0.3848444 
nnet mean 552 : -0.4297795 
nnet RMSE 552 : 0.1514519 


s: 553 
logit 553 : -0.4535098 
logit mean 553 : -0.4248039 
logit RMSE 553 : 0.06758757 

boosting 553 : -0.5883677 
boosting mean 553 : -0.5050815 
boosting RMSE 553 : 0.1603164 

forest 553 : -0.408153 
forest mean 553 : -0.38162 
forest RMSE 553 : 0.05407988 

nnet 553 : -0.5356738 
nnet mean 553 : -0.429971 
nnet RMSE 553 : 0.1514248 


s: 554 
logit 554 : -0.3941288 
logit mean 554 : -0.4247485 
logit RMSE 554 : 0.067527 

boosting 554 : -0.4526099 
boosting mean 554 : -0.5049868 
boosting RMSE 554 : 0.1601872 

forest 554 : -0.2688813 
forest mean 554 : -0.3814165 
forest RMSE 554 : 0.05431746 

nnet 554 : -0.3677505 
nnet mean 554 : -0.4298587 
nnet RMSE 554 : 0.1512943 


s: 555 
logit 555 : -0.4850253 
logit mean 555 : -0.4248571 
logit RMSE 555 : 0.06756261 

boosting 555 : -0.7180446 
boosting mean 555 : -0.5053707 
boosting RMSE 555 : 0.1606112 

forest 555 : -0.4135602 
forest mean 555 : -0.3814745 
forest RMSE 555 : 0.05427156 

nnet 555 : -0.4818216 
nnet mean 555 : -0.4299523 
nnet RMSE 555 : 0.1511979 


s: 556 
logit 556 : -0.3858159 
logit mean 556 : -0.4247869 
logit RMSE 556 : 0.0675045 

boosting 556 : -0.4549297 
boosting mean 556 : -0.50528 
boosting RMSE 556 : 0.1604836 

forest 556 : -0.3092032 
forest mean 556 : -0.3813445 
forest RMSE 556 : 0.05435929 

nnet 556 : -0.1688479 
nnet mean 556 : -0.4294827 
nnet RMSE 556 : 0.1513796 


s: 557 
logit 557 : -0.4294763 
logit mean 557 : -0.4247953 
logit RMSE 557 : 0.06745544 

boosting 557 : -0.5207584 
boosting mean 557 : -0.5053078 
boosting RMSE 557 : 0.1604211 

forest 557 : -0.3834069 
forest mean 557 : -0.3813482 
forest RMSE 557 : 0.05431502 

nnet 557 : -0.3181277 
nnet mean 557 : -0.4292828 
nnet RMSE 557 : 0.1512834 


s: 558 
logit 558 : -0.3619186 
logit mean 558 : -0.4246826 
logit RMSE 558 : 0.06741425 

boosting 558 : -0.5388705 
boosting mean 558 : -0.5053679 
boosting RMSE 558 : 0.1603851 

forest 558 : -0.2731813 
forest mean 558 : -0.3811543 
forest RMSE 558 : 0.05453125 

nnet 558 : -0.3349849 
nnet mean 558 : -0.4291138 
nnet RMSE 558 : 0.1511728 


s: 559 
logit 559 : -0.4379291 
logit mean 559 : -0.4247063 
logit RMSE 559 : 0.06737302 

boosting 559 : -0.5120941 
boosting mean 559 : -0.5053799 
boosting RMSE 559 : 0.1603117 

forest 559 : -0.4246839 
forest mean 559 : -0.3812322 
forest RMSE 559 : 0.05449245 

nnet 559 : -0.5234541 
nnet mean 559 : -0.4292826 
nnet RMSE 559 : 0.1511278 


s: 560 
logit 560 : -0.5231273 
logit mean 560 : -0.4248821 
logit RMSE 560 : 0.06751364 

boosting 560 : -0.5620841 
boosting mean 560 : -0.5054812 
boosting RMSE 560 : 0.1603149 

forest 560 : -0.4234341 
forest mean 560 : -0.3813076 
forest RMSE 560 : 0.05445278 

nnet 560 : -0.4102156 
nnet mean 560 : -0.4292485 
nnet RMSE 560 : 0.1509934 


s: 561 
logit 561 : -0.5491798 
logit mean 561 : -0.4251036 
logit RMSE 561 : 0.06774685 

boosting 561 : -0.6178788 
boosting mean 561 : -0.5056816 
boosting RMSE 561 : 0.1604359 

forest 561 : -0.3661620 
forest mean 561 : -0.3812806 
forest RMSE 561 : 0.05442298 

nnet 561 : -0.5341424 
nnet mean 561 : -0.4294355 
nnet RMSE 561 : 0.1509650 


s: 562 
logit 562 : -0.4611088 
logit mean 562 : -0.4251677 
logit RMSE 562 : 0.06773561 

boosting 562 : -0.5590716 
boosting mean 562 : -0.5057766 
boosting RMSE 562 : 0.1604335 

forest 562 : -0.3125981 
forest mean 562 : -0.3811583 
forest RMSE 562 : 0.05449939 

nnet 562 : -0.4556063 
nnet mean 562 : -0.4294821 
nnet RMSE 562 : 0.1508489 


s: 563 
logit 563 : -0.4475786 
logit mean 563 : -0.4252075 
logit RMSE 563 : 0.06770513 

boosting 563 : -0.4778552 
boosting mean 563 : -0.505727 
boosting RMSE 563 : 0.1603245 

forest 563 : -0.4031808 
forest mean 563 : -0.3811975 
forest RMSE 563 : 0.05445113 

nnet 563 : -0.4071852 
nnet mean 563 : -0.4294425 
nnet RMSE 563 : 0.1507152 


s: 564 
logit 564 : -0.4298443 
logit mean 564 : -0.4252157 
logit RMSE 564 : 0.06765676 

boosting 564 : -0.6372978 
boosting mean 564 : -0.5059602 
boosting RMSE 564 : 0.1604937 

forest 564 : -0.3491271 
forest mean 564 : -0.3811406 
forest RMSE 564 : 0.054445 

nnet 564 : -0.4173097 
nnet mean 564 : -0.429421 
nnet RMSE 564 : 0.1505833 


s: 565 
logit 565 : -0.4525256 
logit mean 565 : -0.4252641 
logit RMSE 565 : 0.06763297 

boosting 565 : -0.3611392 
boosting mean 565 : -0.5057039 
boosting RMSE 565 : 0.1603599 

forest 565 : -0.3740198 
forest mean 565 : -0.381128 
forest RMSE 565 : 0.05440777 

nnet 565 : -0.3819065 
nnet mean 565 : -0.4293369 
nnet RMSE 565 : 0.1504519 


s: 566 
logit 566 : -0.4457991 
logit mean 566 : -0.4253003 
logit RMSE 566 : 0.06760061 

boosting 566 : -0.3912343 
boosting mean 566 : -0.5055017 
boosting RMSE 566 : 0.1602186 

forest 566 : -0.4194494 
forest mean 566 : -0.3811957 
forest RMSE 566 : 0.05436583 

nnet 566 : -0.4719926 
nnet mean 566 : -0.4294122 
nnet RMSE 566 : 0.1503494 


s: 567 
logit 567 : -0.4716512 
logit mean 567 : -0.4253821 
logit RMSE 567 : 0.06760797 

boosting 567 : -0.4535314 
boosting mean 567 : -0.50541 
boosting RMSE 567 : 0.1600930 

forest 567 : -0.4138485 
forest mean 567 : -0.3812533 
forest RMSE 567 : 0.05432099 

nnet 567 : -0.681481 
nnet mean 567 : -0.4298568 
nnet RMSE 567 : 0.1506811 


s: 568 
logit 568 : -0.3705523 
logit mean 568 : -0.4252856 
logit RMSE 568 : 0.06755973 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 568 : -0.8337673 
boosting mean 568 : -0.5059881 
boosting RMSE 568 : 0.1609842 

forest 568 : -0.3506008 
forest mean 568 : -0.3811993 
forest RMSE 568 : 0.05431271 

nnet 568 : -0.5727148 
nnet mean 568 : -0.4301083 
nnet RMSE 568 : 0.1507228 


s: 569 
logit 569 : -0.4641328 
logit mean 569 : -0.4253538 
logit RMSE 569 : 0.06755386 

boosting 569 : -0.6172048 
boosting mean 569 : -0.5061836 
boosting RMSE 569 : 0.1611002 

forest 569 : -0.3871253 
forest mean 569 : -0.3812097 
forest RMSE 569 : 0.05426765 

nnet 569 : -0.3419469 
nnet mean 569 : -0.4299534 
nnet RMSE 569 : 0.1506099 


s: 570 
logit 570 : -0.4373878 
logit mean 570 : -0.4253749 
logit RMSE 570 : 0.06751274 

boosting 570 : -0.3367135 
boosting mean 570 : -0.5058863 
boosting RMSE 570 : 0.1609807 

forest 570 : -0.4631884 
forest mean 570 : -0.3813536 
forest RMSE 570 : 0.05428458 

nnet 570 : -0.2718172 
nnet mean 570 : -0.4296759 
nnet RMSE 570 : 0.1505735 


s: 571 
logit 571 : -0.4636674 
logit mean 571 : -0.425442 
logit RMSE 571 : 0.06750619 

boosting 571 : -0.4449675 
boosting mean 571 : -0.5057796 
boosting RMSE 571 : 0.1608506 

forest 571 : -0.4165382 
forest mean 571 : -0.3814152 
forest RMSE 571 : 0.05424144 

nnet 571 : -0.6161143 
nnet mean 571 : -0.4300024 
nnet RMSE 571 : 0.1507132 


s: 572 
logit 572 : -0.3857655 
logit mean 572 : -0.4253726 
logit RMSE 572 : 0.06744978 

boosting 572 : -0.3308589 
boosting mean 572 : -0.5054738 
boosting RMSE 572 : 0.1607360 

forest 572 : -0.4765551 
forest mean 572 : -0.3815815 
forest RMSE 572 : 0.05428846 

nnet 572 : -0.2772445 
nnet mean 572 : -0.4297354 
nnet RMSE 572 : 0.1506688 


s: 573 
logit 573 : -0.5288388 
logit mean 573 : -0.4255532 
logit RMSE 573 : 0.0676055 

boosting 573 : -0.5907099 
boosting mean 573 : -0.5056225 
boosting RMSE 573 : 0.1607932 

forest 573 : -0.4261982 
forest mean 573 : -0.3816594 
forest RMSE 573 : 0.0542521 

nnet 573 : -0.2496011 
nnet mean 573 : -0.429421 
nnet RMSE 573 : 0.1506684 


s: 574 
logit 574 : -0.4528979 
logit mean 574 : -0.4256009 
logit RMSE 574 : 0.06758266 

boosting 574 : -0.3522674 
boosting mean 574 : -0.5053554 
boosting RMSE 574 : 0.1606654 

forest 574 : -0.3814203 
forest mean 574 : -0.3816590 
forest RMSE 574 : 0.05421037 

nnet 574 : -0.3800223 
nnet mean 574 : -0.429335 
nnet RMSE 574 : 0.1505394 


s: 575 
logit 575 : -0.4225514 
logit mean 575 : -0.4255956 
logit RMSE 575 : 0.06753041 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 575 : -0.5406462 
boosting mean 575 : -0.5054167 
boosting RMSE 575 : 0.1606327 

forest 575 : -0.378811 
forest mean 575 : -0.381654 
forest RMSE 575 : 0.05417042 

nnet 575 : -0.4754998 
nnet mean 575 : -0.4294152 
nnet RMSE 575 : 0.1504414 


s: 576 
logit 576 : -0.4324568 
logit mean 576 : -0.4256075 
logit RMSE 576 : 0.06748532 

boosting 576 : -0.7441986 
boosting mean 576 : -0.5058313 
boosting RMSE 576 : 0.1611327 

forest 576 : -0.4445928 
forest mean 576 : -0.3817633 
forest RMSE 576 : 0.05415526 

nnet 576 : -0.2870076 
nnet mean 576 : -0.429168 
nnet RMSE 576 : 0.1503844 


s: 577 
logit 577 : -0.5042271 
logit mean 577 : -0.4257437 
logit RMSE 577 : 0.06756628 

boosting 577 : -0.5869713 
boosting mean 577 : -0.5059719 
boosting RMSE 577 : 0.1611811 

forest 577 : -0.4452521 
forest mean 577 : -0.3818733 
forest RMSE 577 : 0.0541411 

nnet 577 : -0.7053783 
nnet mean 577 : -0.4296467 
nnet RMSE 577 : 0.1507909 


s: 578 
logit 578 : -0.4135660 
logit mean 578 : -0.4257227 
logit RMSE 578 : 0.06751017 

boosting 578 : -0.5615825 
boosting mean 578 : -0.5060681 
boosting RMSE 578 : 0.1611818 

forest 578 : -0.3267295 
forest mean 578 : -0.3817779 
forest RMSE 578 : 0.05418003 

nnet 578 : -0.3868536 
nnet mean 578 : -0.4295727 
nnet RMSE 578 : 0.1506614 


s: 579 
logit 579 : -0.5187815 
logit mean 579 : -0.4258834 
logit RMSE 579 : 0.06763223 

boosting 579 : -0.4587747 
boosting mean 579 : -0.5059864 
boosting RMSE 579 : 0.1610611 

forest 579 : -0.3834144 
forest mean 579 : -0.3817807 
forest RMSE 579 : 0.05413761 

nnet 579 : -0.4779765 
nnet mean 579 : -0.4296563 
nnet RMSE 579 : 0.1505661 


s: 580 
logit 580 : -0.3978726 
logit mean 580 : -0.4258351 
logit RMSE 580 : 0.06757396 

boosting 580 : -0.6227341 
boosting mean 580 : -0.5061877 
boosting RMSE 580 : 0.1611877 

forest 580 : -0.4153778 
forest mean 580 : -0.3818387 
forest RMSE 580 : 0.05409468 

nnet 580 : -0.1572772 
nnet mean 580 : -0.4291867 
nnet RMSE 580 : 0.1507735 


s: 581 
logit 581 : -0.3743534 
logit mean 581 : -0.4257465 
logit RMSE 581 : 0.06752417 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 581 : -0.4482092 
boosting mean 581 : -0.5060879 
boosting RMSE 581 : 0.1610614 

forest 581 : -0.3301198 
forest mean 581 : -0.3817496 
forest RMSE 581 : 0.05412581 

nnet 581 : -0.2079414 
nnet mean 581 : -0.4288059 
nnet RMSE 581 : 0.1508543 


s: 582 
logit 582 : -0.4503675 
logit mean 582 : -0.4257888 
logit RMSE 582 : 0.06749843 

boosting 582 : -0.6397461 
boosting mean 582 : -0.5063176 
boosting RMSE 582 : 0.1612295 

forest 582 : -0.3465181 
forest mean 582 : -0.3816891 
forest RMSE 582 : 0.05412471 

nnet 582 : -0.2517779 
nnet mean 582 : -0.4285017 
nnet RMSE 582 : 0.1508498 


s: 583 
logit 583 : -0.4170133 
logit mean 583 : -0.4257737 
logit RMSE 583 : 0.0674442 

boosting 583 : -0.2616968 
boosting mean 583 : -0.505898 
boosting RMSE 583 : 0.1611930 

forest 583 : -0.4234875 
forest mean 583 : -0.3817608 
forest RMSE 583 : 0.05408702 

nnet 583 : -0.5933851 
nnet mean 583 : -0.4287845 
nnet RMSE 583 : 0.1509330 


s: 584 
logit 584 : -0.5059406 
logit mean 584 : -0.425911 
logit RMSE 584 : 0.06752887 

boosting 584 : -0.5366767 
boosting mean 584 : -0.5059507 
boosting RMSE 584 : 0.1611542 

forest 584 : -0.3887439 
forest mean 584 : -0.3817728 
forest RMSE 584 : 0.0540427 

nnet 584 : -0.3448006 
nnet mean 584 : -0.4286407 
nnet RMSE 584 : 0.1508210 


s: 585 
logit 585 : -0.3850928 
logit mean 585 : -0.4258412 
logit RMSE 585 : 0.06747395 

boosting 585 : -0.5313798 
boosting mean 585 : -0.5059942 
boosting RMSE 585 : 0.1611080 

forest 585 : -0.4039429 
forest mean 585 : -0.3818107 
forest RMSE 585 : 0.05399673 

nnet 585 : -0.3325321 
nnet mean 585 : -0.4284764 
nnet RMSE 585 : 0.1507179 


s: 586 
logit 586 : -0.4185559 
logit mean 586 : -0.4258288 
logit RMSE 586 : 0.06742071 

boosting 586 : -0.6169721 
boosting mean 586 : -0.5061836 
boosting RMSE 586 : 0.1612198 

forest 586 : -0.4122521 
forest mean 586 : -0.3818626 
forest RMSE 586 : 0.05395302 

nnet 586 : -0.240044 
nnet mean 586 : -0.4281548 
nnet RMSE 586 : 0.1507341 


s: 587 
logit 587 : -0.5376131 
logit mean 587 : -0.4260192 
logit RMSE 587 : 0.06760229 

boosting 587 : -0.2087052 
boosting mean 587 : -0.5056768 
boosting RMSE 587 : 0.1612758 

forest 587 : -0.3601051 
forest mean 587 : -0.3818255 
forest RMSE 587 : 0.05393218 

nnet 587 : -0.3577794 
nnet mean 587 : -0.428035 
nnet RMSE 587 : 0.1506158 


s: 588 
logit 588 : -0.3909467 
logit mean 588 : -0.4259596 
logit RMSE 588 : 0.06754581 

boosting 588 : -0.4481684 
boosting mean 588 : -0.505579 
boosting RMSE 588 : 0.1611508 

forest 588 : -0.3762721 
forest mean 588 : -0.3818161 
forest RMSE 588 : 0.05389519 

nnet 588 : -0.5888816 
nnet mean 588 : -0.4283085 
nnet RMSE 588 : 0.1506891 


s: 589 
logit 589 : -0.4869299 
logit mean 589 : -0.4260631 
logit RMSE 589 : 0.06758343 

boosting 589 : -0.4170323 
boosting mean 589 : -0.5054286 
boosting RMSE 589 : 0.1610155 

forest 589 : -0.396877 
forest mean 589 : -0.3818417 
forest RMSE 589 : 0.05384957 

nnet 589 : -0.3931739 
nnet mean 589 : -0.4282489 
nnet RMSE 589 : 0.1505614 


s: 590 
logit 590 : -0.4281573 
logit mean 590 : -0.4260666 
logit RMSE 590 : 0.06753608 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 590 : -0.6211764 
boosting mean 590 : -0.5056248 
boosting RMSE 590 : 0.1611365 

forest 590 : -0.4025933 
forest mean 590 : -0.3818768 
forest RMSE 590 : 0.05380402 

nnet 590 : -0.4945497 
nnet mean 590 : -0.4283612 
nnet RMSE 590 : 0.1504841 


s: 591 
logit 591 : -0.4813512 
logit mean 591 : -0.4261602 
logit RMSE 591 : 0.06756185 

boosting 591 : -0.7396005 
boosting mean 591 : -0.5060207 
boosting RMSE 591 : 0.161605 

forest 591 : -0.3564332 
forest mean 591 : -0.3818338 
forest RMSE 591 : 0.05378834 

nnet 591 : -0.4301059 
nnet mean 591 : -0.4283642 
nnet RMSE 591 : 0.1503618 


s: 592 
logit 592 : -0.4366761 
logit mean 592 : -0.4261779 
logit RMSE 592 : 0.06752159 

boosting 592 : -0.5853774 
boosting mean 592 : -0.5061548 
boosting RMSE 592 : 0.1616481 

forest 592 : -0.344032 
forest mean 592 : -0.3817699 
forest RMSE 592 : 0.0537921 

nnet 592 : -0.6924417 
nnet mean 592 : -0.4288103 
nnet RMSE 592 : 0.1507148 


s: 593 
logit 593 : -0.4818764 
logit mean 593 : -0.4262719 
logit RMSE 593 : 0.06754836 

boosting 593 : -0.806761 
boosting mean 593 : -0.5066617 
boosting RMSE 593 : 0.1623732 

forest 593 : -0.3568151 
forest mean 593 : -0.3817278 
forest RMSE 593 : 0.05377597 

nnet 593 : -0.4691531 
nnet mean 593 : -0.4288783 
nnet RMSE 593 : 0.1506145 


s: 594 
logit 594 : -0.3773425 
logit mean 594 : -0.4261895 
logit RMSE 594 : 0.06749788 

boosting 594 : -0.4097675 
boosting mean 594 : -0.5064986 
boosting RMSE 594 : 0.1622370 

forest 594 : -0.3124291 
forest mean 594 : -0.3816112 
forest RMSE 594 : 0.05385069 

nnet 594 : -0.4694503 
nnet mean 594 : -0.4289466 
nnet RMSE 594 : 0.1505146 


s: 595 
logit 595 : -0.4003679 
logit mean 595 : -0.4261461 
logit RMSE 595 : 0.06744114 

boosting 595 : -0.9456485 
boosting mean 595 : -0.5072366 
boosting RMSE 595 : 0.1636367 

forest 595 : -0.4113132 
forest mean 595 : -0.3816611 
forest RMSE 595 : 0.05380742 

nnet 595 : -1.060186 
nnet mean 595 : -0.4300075 
nnet RMSE 595 : 0.1528041 


s: 596 
logit 596 : -0.5007509 
logit mean 596 : -0.4262713 
logit RMSE 596 : 0.06751079 

boosting 596 : -0.5978494 
boosting mean 596 : -0.5073887 
boosting RMSE 596 : 0.1637001 

forest 596 : -0.3696278 
forest mean 596 : -0.3816409 
forest RMSE 596 : 0.05377665 

nnet 596 : -0.2005176 
nnet mean 596 : -0.4296224 
nnet RMSE 596 : 0.1528943 


s: 597 
logit 597 : -0.5596515 
logit mean 597 : -0.4264947 
logit RMSE 597 : 0.06776996 

boosting 597 : -0.3200624 
boosting mean 597 : -0.5070749 
boosting RMSE 597 : 0.1635957 

forest 597 : -0.4000107 
forest mean 597 : -0.3816717 
forest RMSE 597 : 0.0537316 

nnet 597 : -0.4398993 
nnet mean 597 : -0.4296397 
nnet RMSE 597 : 0.1527749 


s: 598 
logit 598 : -0.3955838 
logit mean 598 : -0.426443 
logit RMSE 598 : 0.06771351 

boosting 598 : -0.4156626 
boosting mean 598 : -0.506922 
boosting RMSE 598 : 0.1634601 

forest 598 : -0.4736692 
forest mean 598 : -0.3818255 
forest RMSE 598 : 0.05377111 

nnet 598 : -0.2276482 
nnet mean 598 : -0.4293019 
nnet RMSE 598 : 0.1528098 


s: 599 
logit 599 : -0.4313427 
logit mean 599 : -0.4264512 
logit RMSE 599 : 0.06766909 

boosting 599 : -0.5259226 
boosting mean 599 : -0.5069537 
boosting RMSE 599 : 0.1634046 

forest 599 : -0.4314473 
forest mean 599 : -0.3819084 
forest RMSE 599 : 0.05374157 

nnet 599 : -0.6202363 
nnet mean 599 : -0.4296206 
nnet RMSE 599 : 0.1529471 


s: 600 
logit 600 : -0.431728 
logit mean 600 : -0.42646 
logit RMSE 600 : 0.06762508 

boosting 600 : -0.5394189 
boosting mean 600 : -0.5070079 
boosting RMSE 600 : 0.1633676 

forest 600 : -0.4226166 
forest mean 600 : -0.3819762 
forest RMSE 600 : 0.0537047 

nnet 600 : -0.4053355 
nnet mean 600 : -0.4295802 
nnet RMSE 600 : 0.1528198 


s: 601 
logit 601 : -0.5387991 
logit mean 601 : -0.4266469 
logit RMSE 601 : 0.06780558 

boosting 601 : -0.7432496 
boosting mean 601 : -0.5074009 
boosting RMSE 601 : 0.163831 

forest 601 : -0.4723164 
forest mean 601 : -0.3821265 
forest RMSE 601 : 0.05374102 

nnet 601 : -0.542243 
nnet mean 601 : -0.4297676 
nnet RMSE 601 : 0.1528028 


s: 602 
logit 602 : -0.3902031 
logit mean 602 : -0.4265864 
logit RMSE 602 : 0.06775042 

boosting 602 : -0.2462572 
boosting mean 602 : -0.5069671 
boosting RMSE 602 : 0.1638148 

forest 602 : -0.3313081 
forest mean 602 : -0.3820421 
forest RMSE 602 : 0.05376931 

nnet 602 : -0.5147642 
nnet mean 602 : -0.4299088 
nnet RMSE 602 : 0.1527474 


s: 603 
logit 603 : -0.4471686 
logit mean 603 : -0.4266205 
logit RMSE 603 : 0.06772146 

boosting 603 : -0.3928907 
boosting mean 603 : -0.506778 
boosting RMSE 603 : 0.1636791 

forest 603 : -0.3263033 
forest mean 603 : -0.3819497 
forest RMSE 603 : 0.05380846 

nnet 603 : -0.1861390 
nnet mean 603 : -0.4295046 
nnet RMSE 603 : 0.152869 


s: 604 
logit 604 : -0.3616989 
logit mean 604 : -0.426513 
logit RMSE 604 : 0.06768333 

boosting 604 : -0.6480243 
boosting mean 604 : -0.5070118 
boosting RMSE 604 : 0.1638547 

forest 604 : -0.3386096 
forest mean 604 : -0.3818779 
forest RMSE 604 : 0.0538219 

nnet 604 : -0.3651793 
nnet mean 604 : -0.4293981 
nnet RMSE 604 : 0.1527490 


s: 605 
logit 605 : -0.5001425 
logit mean 605 : -0.4266347 
logit RMSE 605 : 0.06774981 

boosting 605 : -0.6874608 
boosting mean 605 : -0.5073101 
boosting RMSE 605 : 0.1641358 

forest 605 : -0.346752 
forest mean 605 : -0.3818199 
forest RMSE 605 : 0.05382095 

nnet 605 : -0.5261336 
nnet mean 605 : -0.4295579 
nnet RMSE 605 : 0.1527088 


s: 606 
logit 606 : -0.5325677 
logit mean 606 : -0.4268095 
logit RMSE 606 : 0.06790775 

boosting 606 : -0.4424152 
boosting mean 606 : -0.507203 
boosting RMSE 606 : 0.1640094 

forest 606 : -0.405251 
forest mean 606 : -0.3818585 
forest RMSE 606 : 0.05377695 

nnet 606 : -0.5429525 
nnet mean 606 : -0.4297451 
nnet RMSE 606 : 0.1526932 


s: 607 
logit 607 : -0.5030627 
logit mean 607 : -0.4269351 
logit RMSE 607 : 0.06798062 

boosting 607 : -0.586694 
boosting mean 607 : -0.5073339 
boosting RMSE 607 : 0.1640493 

forest 607 : -0.3480928 
forest mean 607 : -0.3818029 
forest RMSE 607 : 0.05377393 

nnet 607 : -0.5513395 
nnet mean 607 : -0.4299454 
nnet RMSE 607 : 0.152691 


s: 608 
logit 608 : -0.4371926 
logit mean 608 : -0.426952 
logit RMSE 608 : 0.06794144 

boosting 608 : -0.5034699 
boosting mean 608 : -0.5073276 
boosting RMSE 608 : 0.1639680 

forest 608 : -0.3498526 
forest mean 608 : -0.3817504 
forest RMSE 608 : 0.05376816 

nnet 608 : -0.4684266 
nnet mean 608 : -0.4300087 
nnet RMSE 608 : 0.1525906 


s: 609 
logit 609 : -0.4599402 
logit mean 609 : -0.4270062 
logit RMSE 609 : 0.06792907 

boosting 609 : -0.5569202 
boosting mean 609 : -0.507409 
boosting RMSE 609 : 0.1639567 

forest 609 : -0.3706107 
forest mean 609 : -0.3817321 
forest RMSE 609 : 0.0537372 

nnet 609 : -0.5385477 
nnet mean 609 : -0.4301869 
nnet RMSE 609 : 0.1525686 


s: 610 
logit 610 : -0.5133197 
logit mean 610 : -0.4271477 
logit RMSE 610 : 0.06802827 

boosting 610 : -0.4395174 
boosting mean 610 : -0.5072977 
boosting RMSE 610 : 0.1638301 

forest 610 : -0.4719203 
forest mean 610 : -0.3818799 
forest RMSE 610 : 0.05377204 

nnet 610 : -0.3274789 
nnet mean 610 : -0.4300185 
nnet RMSE 610 : 0.1524718 


s: 611 
logit 611 : -0.4000802 
logit mean 611 : -0.4271034 
logit RMSE 611 : 0.06797258 

boosting 611 : -0.3779157 
boosting mean 611 : -0.507086 
boosting RMSE 611 : 0.1636984 

forest 611 : -0.4730195 
forest mean 611 : -0.3820291 
forest RMSE 611 : 0.05380916 

nnet 611 : -0.2898427 
nnet mean 611 : -0.4297891 
nnet RMSE 611 : 0.1524121 


s: 612 
logit 612 : -0.4842929 
logit mean 612 : -0.4271968 
logit RMSE 612 : 0.06800244 

boosting 612 : -0.5149011 
boosting mean 612 : -0.5070987 
boosting RMSE 612 : 0.1636305 

forest 612 : -0.3451067 
forest mean 612 : -0.3819687 
forest RMSE 612 : 0.05381095 

nnet 612 : -0.3074629 
nnet mean 612 : -0.4295892 
nnet RMSE 612 : 0.1523335 


s: 613 
logit 613 : -0.4987862 
logit mean 613 : -0.4273136 
logit RMSE 613 : 0.068064 

boosting 613 : -0.5577596 
boosting mean 613 : -0.5071814 
boosting RMSE 613 : 0.1636211 

forest 613 : -0.3913433 
forest mean 613 : -0.381984 
forest RMSE 613 : 0.05376818 

nnet 613 : -0.3129287 
nnet mean 613 : -0.4293989 
nnet RMSE 613 : 0.1522498 


s: 614 
logit 614 : -0.4359018 
logit mean 614 : -0.4273276 
logit RMSE 614 : 0.06802398 

boosting 614 : -0.5068773 
boosting mean 614 : -0.5071809 
boosting RMSE 614 : 0.1635447 

forest 614 : -0.356195 
forest mean 614 : -0.381942 
forest RMSE 614 : 0.05375346 

nnet 614 : -0.2982552 
nnet mean 614 : -0.4291853 
nnet RMSE 614 : 0.1521812 


s: 615 
logit 615 : -0.357486 
logit mean 615 : -0.427214 
logit RMSE 615 : 0.06799027 

boosting 615 : -0.5046585 
boosting mean 615 : -0.5071768 
boosting RMSE 615 : 0.1634662 

forest 615 : -0.3989464 
forest mean 615 : -0.3819697 
forest RMSE 615 : 0.05370975 

nnet 615 : -0.4917141 
nnet mean 615 : -0.429287 
nnet RMSE 615 : 0.1521024 


s: 616 
logit 616 : -0.4387882 
logit mean 616 : -0.4272328 
logit RMSE 616 : 0.06795303 

boosting 616 : -0.3731515 
boosting mean 616 : -0.5069592 
boosting RMSE 616 : 0.1633370 

forest 616 : -0.32406 
forest mean 616 : -0.3818757 
forest RMSE 616 : 0.05375329 

nnet 616 : -0.4230051 
nnet mean 616 : -0.4292768 
nnet RMSE 616 : 0.1519817 


s: 617 
logit 617 : -0.4665487 
logit mean 617 : -0.4272965 
logit RMSE 617 : 0.06795078 

boosting 617 : -0.4260287 
boosting mean 617 : -0.506828 
boosting RMSE 617 : 0.163208 

forest 617 : -0.4779844 
forest mean 617 : -0.3820314 
forest RMSE 617 : 0.05380139 

nnet 617 : -0.5832655 
nnet mean 617 : -0.4295264 
nnet RMSE 617 : 0.1520376 


s: 618 
logit 618 : -0.3557275 
logit mean 618 : -0.4271807 
logit RMSE 618 : 0.06791913 

boosting 618 : -0.4291873 
boosting mean 618 : -0.5067024 
boosting RMSE 618 : 0.1630801 

forest 618 : -0.2862849 
forest mean 618 : -0.3818765 
forest RMSE 618 : 0.05395211 

nnet 618 : -0.5166684 
nnet mean 618 : -0.4296674 
nnet RMSE 618 : 0.1519870 


s: 619 
logit 619 : -0.4041253 
logit mean 619 : -0.4271435 
logit RMSE 619 : 0.06786445 

boosting 619 : -0.4826111 
boosting mean 619 : -0.5066635 
boosting RMSE 619 : 0.1629822 

forest 619 : -0.3405893 
forest mean 619 : -0.3818098 
forest RMSE 619 : 0.05396138 

nnet 619 : -0.7385624 
nnet mean 619 : -0.4301664 
nnet RMSE 619 : 0.1524727 


s: 620 
logit 620 : -0.4431179 
logit mean 620 : -0.4271693 
logit RMSE 620 : 0.06783181 

boosting 620 : -0.4595277 
boosting mean 620 : -0.5065875 
boosting RMSE 620 : 0.1628682 

forest 620 : -0.4820476 
forest mean 620 : -0.3819715 
forest RMSE 620 : 0.05401843 

nnet 620 : -0.627783 
nnet mean 620 : -0.4304851 
nnet RMSE 620 : 0.1526241 


s: 621 
logit 621 : -0.4621817 
logit mean 621 : -0.4272256 
logit RMSE 621 : 0.06782309 

boosting 621 : -0.5990405 
boosting mean 621 : -0.5067363 
boosting RMSE 621 : 0.1629329 

forest 621 : -0.3319234 
forest mean 621 : -0.3818909 
forest RMSE 621 : 0.05404401 

nnet 621 : -0.5834313 
nnet mean 621 : -0.4307314 
nnet RMSE 621 : 0.1526787 


s: 622 
logit 622 : -0.3915383 
logit mean 622 : -0.4271683 
logit RMSE 622 : 0.0677694 

boosting 622 : -0.4724983 
boosting mean 622 : -0.5066813 
boosting RMSE 622 : 0.1628278 

forest 622 : -0.4067186 
forest mean 622 : -0.3819308 
forest RMSE 622 : 0.05400122 

nnet 622 : -0.3137260 
nnet mean 622 : -0.4305433 
nnet RMSE 622 : 0.1525951 


s: 623 
logit 623 : -0.2932297 
logit mean 623 : -0.4269533 
logit RMSE 623 : 0.06784996 

boosting 623 : -0.5192824 
boosting mean 623 : -0.5067015 
boosting RMSE 623 : 0.1627673 

forest 623 : -0.3835782 
forest mean 623 : -0.3819335 
forest RMSE 623 : 0.05396188 

nnet 623 : -0.3172496 
nnet mean 623 : -0.4303615 
nnet RMSE 623 : 0.1525086 


s: 624 
logit 624 : -0.3003386 
logit mean 624 : -0.4267504 
logit RMSE 624 : 0.06791286 

boosting 624 : -0.3676973 
boosting mean 624 : -0.5064788 
boosting RMSE 624 : 0.1626419 

forest 624 : -0.2600904 
forest mean 624 : -0.3817382 
forest RMSE 624 : 0.05420874 

nnet 624 : -0.2119769 
nnet mean 624 : -0.4300115 
nnet RMSE 624 : 0.1525722 


s: 625 
logit 625 : -0.4174210 
logit mean 625 : -0.4267354 
logit RMSE 625 : 0.06786209 

boosting 625 : -0.5219408 
boosting mean 625 : -0.5065035 
boosting RMSE 625 : 0.1625850 

forest 625 : -0.3791133 
forest mean 625 : -0.381734 
forest RMSE 625 : 0.0541718 

nnet 625 : -0.3913619 
nnet mean 625 : -0.4299497 
nnet RMSE 625 : 0.1524504 


s: 626 
logit 626 : -0.3680427 
logit mean 626 : -0.4266417 
logit RMSE 626 : 0.0678199 

boosting 626 : -0.4018713 
boosting mean 626 : -0.5063364 
boosting RMSE 626 : 0.1624551 

forest 626 : -0.4142288 
forest mean 626 : -0.3817859 
forest RMSE 626 : 0.0541315 

nnet 626 : -0.3413112 
nnet mean 626 : -0.4298081 
nnet RMSE 626 : 0.1523467 


s: 627 
logit 627 : -0.3144768 
logit mean 627 : -0.4264628 
logit RMSE 627 : 0.0678518 

boosting 627 : -0.5013951 
boosting mean 627 : -0.5063285 
boosting RMSE 627 : 0.1623760 

forest 627 : -0.4156397 
forest mean 627 : -0.3818399 
forest RMSE 627 : 0.05409192 

nnet 627 : -0.7081432 
nnet mean 627 : -0.430252 
nnet RMSE 627 : 0.1527218 


s: 628 
logit 628 : -0.4391177 
logit mean 628 : -0.4264829 
logit RMSE 628 : 0.06781573 

boosting 628 : -0.4433711 
boosting mean 628 : -0.5062282 
boosting RMSE 628 : 0.1622559 

forest 628 : -0.4061564 
forest mean 628 : -0.3818786 
forest RMSE 628 : 0.0540494 

nnet 628 : -0.439055 
nnet mean 628 : -0.430266 
nnet RMSE 628 : 0.1526081 


s: 629 
logit 629 : -0.4224621 
logit mean 629 : -0.4264765 
logit RMSE 629 : 0.06776772 

boosting 629 : -0.4452229 
boosting mean 629 : -0.5061312 
boosting RMSE 629 : 0.1621369 

forest 629 : -0.3508929 
forest mean 629 : -0.3818294 
forest RMSE 629 : 0.0540419 

nnet 629 : -0.4239299 
nnet mean 629 : -0.4302559 
nnet RMSE 629 : 0.1524897 


s: 630 
logit 630 : -0.4514348 
logit mean 630 : -0.4265162 
logit RMSE 630 : 0.06774491 

boosting 630 : -0.3601404 
boosting mean 630 : -0.5058995 
boosting RMSE 630 : 0.1620159 

forest 630 : -0.3904115 
forest mean 630 : -0.381843 
forest RMSE 630 : 0.05400034 

nnet 630 : -0.3250898 
nnet mean 630 : -0.430089 
nnet RMSE 630 : 0.1523979 


s: 631 
logit 631 : -0.4323195 
logit mean 631 : -0.4265254 
logit RMSE 631 : 0.06770344 

boosting 631 : -0.3755321 
boosting mean 631 : -0.5056929 
boosting RMSE 631 : 0.1618904 

forest 631 : -0.3046376 
forest mean 631 : -0.3817206 
forest RMSE 631 : 0.05409092 

nnet 631 : -0.2575348 
nnet mean 631 : -0.4298155 
nnet RMSE 631 : 0.1523826 


s: 632 
logit 632 : -0.3555168 
logit mean 632 : -0.426413 
logit RMSE 632 : 0.06767299 

boosting 632 : -0.6506714 
boosting mean 632 : -0.5059223 
boosting RMSE 632 : 0.1620693 

forest 632 : -0.3814868 
forest mean 632 : -0.3817203 
forest RMSE 632 : 0.05405313 

nnet 632 : -0.5960858 
nnet mean 632 : -0.4300786 
nnet RMSE 632 : 0.1524617 


s: 633 
logit 633 : -0.4541274 
logit mean 633 : -0.4264568 
logit RMSE 633 : 0.06765373 

boosting 633 : -0.5649799 
boosting mean 633 : -0.5060156 
boosting RMSE 633 : 0.1620739 

forest 633 : -0.3853299 
forest mean 633 : -0.3817260 
forest RMSE 633 : 0.05401356 

nnet 633 : -0.3443399 
nnet mean 633 : -0.4299432 
nnet RMSE 633 : 0.1523573 


s: 634 
logit 634 : -0.4001555 
logit mean 634 : -0.4264153 
logit RMSE 634 : 0.06760036 

boosting 634 : -0.5303111 
boosting mean 634 : -0.5060539 
boosting RMSE 634 : 0.1620288 

forest 634 : -0.3825544 
forest mean 634 : -0.3817273 
forest RMSE 634 : 0.05397539 

nnet 634 : -0.2702037 
nnet mean 634 : -0.4296912 
nnet RMSE 634 : 0.1523243 


s: 635 
logit 635 : -0.5389523 
logit mean 635 : -0.4265925 
logit RMSE 635 : 0.0677718 

boosting 635 : -0.6254263 
boosting mean 635 : -0.5062419 
boosting RMSE 635 : 0.1621481 

forest 635 : -0.3692838 
forest mean 635 : -0.3817077 
forest RMSE 635 : 0.05394665 

nnet 635 : -0.432934 
nnet mean 635 : -0.4296963 
nnet RMSE 635 : 0.1522099 


s: 636 
logit 636 : -0.4042771 
logit mean 636 : -0.4265574 
logit RMSE 636 : 0.06771872 

boosting 636 : -0.3598100 
boosting mean 636 : -0.5060117 
boosting RMSE 636 : 0.1620284 

forest 636 : -0.3815888 
forest mean 636 : -0.3817075 
forest RMSE 636 : 0.05390916 

nnet 636 : -0.4318995 
nnet mean 636 : -0.4296998 
nnet RMSE 636 : 0.1520955 


s: 637 
logit 637 : -0.3144016 
logit mean 637 : -0.4263814 
logit RMSE 637 : 0.06775048 

boosting 637 : -0.5780593 
boosting mean 637 : -0.5061248 
boosting RMSE 637 : 0.1620548 

forest 637 : -0.3408722 
forest mean 637 : -0.3816434 
forest RMSE 637 : 0.05391775 

nnet 637 : -0.5130216 
nnet mean 637 : -0.4298306 
nnet RMSE 637 : 0.152042 


s: 638 
logit 638 : -0.4565815 
logit mean 638 : -0.4264287 
logit RMSE 638 : 0.06773442 

boosting 638 : -0.3965675 
boosting mean 638 : -0.5059531 
boosting RMSE 638 : 0.1619278 

forest 638 : -0.397343 
forest mean 638 : -0.381668 
forest RMSE 638 : 0.05387558 

nnet 638 : -0.6028311 
nnet mean 638 : -0.4301018 
nnet RMSE 638 : 0.1521349 


s: 639 
logit 639 : -0.4553329 
logit mean 639 : -0.4264739 
logit RMSE 639 : 0.06771678 

boosting 639 : -0.7000182 
boosting mean 639 : -0.5062568 
boosting RMSE 639 : 0.1622358 

forest 639 : -0.4355513 
forest mean 639 : -0.3817523 
forest RMSE 639 : 0.05385178 

nnet 639 : -0.5095979 
nnet mean 639 : -0.4302262 
nnet RMSE 639 : 0.1520776 


s: 640 
logit 640 : -0.3976445 
logit mean 640 : -0.4264289 
logit RMSE 640 : 0.06766392 

boosting 640 : -0.3354312 
boosting mean 640 : -0.5059898 
boosting RMSE 640 : 0.1621291 

forest 640 : -0.3227722 
forest mean 640 : -0.3816601 
forest RMSE 640 : 0.05389621 

nnet 640 : -0.7034699 
nnet mean 640 : -0.4306531 
nnet RMSE 640 : 0.1524315 


s: 641 
logit 641 : -0.5119242 
logit mean 641 : -0.4265623 
logit RMSE 641 : 0.0677555 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 641 : -0.424858 
boosting mean 641 : -0.5058633 
boosting RMSE 641 : 0.1620055 

forest 641 : -0.4872414 
forest mean 641 : -0.3818249 
forest RMSE 641 : 0.05396428 

nnet 641 : -0.4221775 
nnet mean 641 : -0.4306399 
nnet RMSE 641 : 0.1523151 


s: 642 
logit 642 : -0.4661691 
logit mean 642 : -0.426624 
logit RMSE 642 : 0.06775305 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 642 : -0.5013739 
boosting mean 642 : -0.5058563 
boosting RMSE 642 : 0.1619287 

forest 642 : -0.3979232 
forest mean 642 : -0.3818499 
forest RMSE 642 : 0.0539223 

nnet 642 : -0.5445393 
nnet mean 642 : -0.4308173 
nnet RMSE 642 : 0.1523033 


s: 643 
logit 643 : -0.5335587 
logit mean 643 : -0.4267903 
logit RMSE 643 : 0.06790492 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 643 : -0.601045 
boosting mean 643 : -0.5060043 
boosting RMSE 643 : 0.1619969 

forest 643 : -0.3703182 
forest mean 643 : -0.381832 
forest RMSE 643 : 0.05389307 

nnet 643 : -0.1445356 
nnet mean 643 : -0.4303721 
nnet RMSE 643 : 0.1525179 


s: 644 
logit 644 : -0.4197089 
logit mean 644 : -0.4267793 
logit RMSE 644 : 0.06785663 

boosting 644 : -0.3874042 
boosting mean 644 : -0.5058202 
boosting RMSE 644 : 0.1618718 

forest 644 : -0.4174602 
forest mean 644 : -0.3818873 
forest RMSE 644 : 0.0538556 

nnet 644 : -0.2624624 
nnet mean 644 : -0.4301113 
nnet RMSE 644 : 0.1524958 


s: 645 
logit 645 : -0.4234412 
logit mean 645 : -0.4267741 
logit RMSE 645 : 0.06781029 

boosting 645 : -0.4929694 
boosting mean 645 : -0.5058002 
boosting RMSE 645 : 0.1617877 

forest 645 : -0.4073181 
forest mean 645 : -0.3819268 
forest RMSE 645 : 0.05381461 

nnet 645 : -0.510963 
nnet mean 645 : -0.4302367 
nnet RMSE 645 : 0.1524401 


s: 646 
logit 646 : -0.3742266 
logit mean 646 : -0.4266928 
logit RMSE 646 : 0.06776537 

boosting 646 : -0.524476 
boosting mean 646 : -0.5058291 
boosting RMSE 646 : 0.1617366 

forest 646 : -0.4091386 
forest mean 646 : -0.3819689 
forest RMSE 646 : 0.05377414 

nnet 646 : -0.07768825 
nnet mean 646 : -0.4296909 
nnet RMSE 646 : 0.1528490 


s: 647 
logit 647 : -0.469643 
logit mean 647 : -0.4267591 
logit RMSE 647 : 0.06776831 

boosting 647 : -0.6627118 
boosting mean 647 : -0.5060716 
boosting RMSE 647 : 0.1619413 

forest 647 : -0.4904438 
forest mean 647 : -0.3821365 
forest RMSE 647 : 0.05385009 

nnet 647 : -0.5485291 
nnet mean 647 : -0.4298746 
nnet RMSE 647 : 0.1528425 


s: 648 
logit 648 : -0.3612898 
logit mean 648 : -0.4266581 
logit RMSE 648 : 0.06773307 

boosting 648 : -0.4566906 
boosting mean 648 : -0.5059954 
boosting RMSE 648 : 0.1618316 

forest 648 : -0.3682739 
forest mean 648 : -0.3821151 
forest RMSE 648 : 0.05382296 

nnet 648 : -0.1784471 
nnet mean 648 : -0.4294866 
nnet RMSE 648 : 0.1529723 


s: 649 
logit 649 : -0.5012995 
logit mean 649 : -0.4267731 
logit RMSE 649 : 0.06779758 

boosting 649 : -0.5128649 
boosting mean 649 : -0.506006 
boosting RMSE 649 : 0.1617675 

forest 649 : -0.4674688 
forest mean 649 : -0.3822467 
forest RMSE 649 : 0.05384664 

nnet 649 : -0.4391975 
nnet mean 649 : -0.4295016 
nnet RMSE 649 : 0.1528621 


s: 650 
logit 650 : -0.4428804 
logit mean 650 : -0.4267979 
logit RMSE 650 : 0.06776628 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 650 : -0.6182129 
boosting mean 650 : -0.5061786 
boosting RMSE 650 : 0.1618695 

forest 650 : -0.3276823 
forest mean 650 : -0.3821627 
forest RMSE 650 : 0.05387992 

nnet 650 : -0.3320549 
nnet mean 650 : -0.4293517 
nnet RMSE 650 : 0.1527677 


s: 651 
logit 651 : -0.4490492 
logit mean 651 : -0.4268321 
logit RMSE 651 : 0.0677415 

boosting 651 : -0.7293937 
boosting mean 651 : -0.5065215 
boosting RMSE 651 : 0.1622595 

forest 651 : -0.3004817 
forest mean 651 : -0.3820372 
forest RMSE 651 : 0.05397963 

nnet 651 : -0.7043074 
nnet mean 651 : -0.429774 
nnet RMSE 651 : 0.1531156 


s: 652 
logit 652 : -0.505186 
logit mean 652 : -0.4269522 
logit RMSE 652 : 0.06781476 

boosting 652 : -0.445072 
boosting mean 652 : -0.5064273 
boosting RMSE 652 : 0.1621447 

forest 652 : -0.3096408 
forest mean 652 : -0.3819262 
forest RMSE 652 : 0.05405417 

nnet 652 : -0.5044556 
nnet mean 652 : -0.4298886 
nnet RMSE 652 : 0.1530528 


s: 653 
logit 653 : -0.4118712 
logit mean 653 : -0.4269292 
logit RMSE 653 : 0.0677644 

boosting 653 : -0.5387064 
boosting mean 653 : -0.5064767 
boosting RMSE 653 : 0.1621114 

forest 653 : -0.3727998 
forest mean 653 : -0.3819122 
forest RMSE 653 : 0.05402326 

nnet 653 : -0.3263627 
nnet mean 653 : -0.42973 
nnet RMSE 653 : 0.1529627 


s: 654 
logit 654 : -0.3845436 
logit mean 654 : -0.4268643 
logit RMSE 654 : 0.06771527 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 654 : -0.4690418 
boosting mean 654 : -0.5064194 
boosting RMSE 654 : 0.1620099 

forest 654 : -0.3139604 
forest mean 654 : -0.3818083 
forest RMSE 654 : 0.05408668 

nnet 654 : -0.1537597 
nnet mean 654 : -0.4293081 
nnet RMSE 654 : 0.1531487 


s: 655 
logit 655 : -0.4171201 
logit mean 655 : -0.4268495 
logit RMSE 655 : 0.06766687 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 655 : -0.2399220 
boosting mean 655 : -0.5060126 
boosting RMSE 655 : 0.1620069 

forest 655 : -0.3506655 
forest mean 655 : -0.3817608 
forest RMSE 655 : 0.05407974 

nnet 655 : -0.3800472 
nnet mean 655 : -0.4292328 
nnet RMSE 655 : 0.1530337 


s: 656 
logit 656 : -0.3401461 
logit mean 656 : -0.4267173 
logit RMSE 656 : 0.06765565 

boosting 656 : -0.386809 
boosting mean 656 : -0.5058309 
boosting RMSE 656 : 0.1618842 

forest 656 : -0.3432266 
forest mean 656 : -0.3817020 
forest RMSE 656 : 0.05408395 

nnet 656 : -0.6044017 
nnet mean 656 : -0.4294999 
nnet RMSE 656 : 0.1531252 


s: 657 
logit 657 : -0.5018257 
logit mean 657 : -0.4268316 
logit RMSE 657 : 0.06772076 

boosting 657 : -0.5379796 
boosting mean 657 : -0.5058798 
boosting RMSE 657 : 0.1618505 

forest 657 : -0.4131548 
forest mean 657 : -0.3817499 
forest RMSE 657 : 0.05404521 

nnet 657 : -0.5585129 
nnet mean 657 : -0.4296962 
nnet RMSE 657 : 0.1531335 


s: 658 
logit 658 : -0.3216355 
logit mean 658 : -0.4266717 
logit RMSE 658 : 0.0677382 

boosting 658 : -0.5516887 
boosting mean 658 : -0.5059494 
boosting RMSE 658 : 0.1618356 

forest 658 : -0.2651969 
forest mean 658 : -0.3815728 
forest RMSE 658 : 0.05425922 

nnet 658 : -0.5382234 
nnet mean 658 : -0.4298612 
nnet RMSE 658 : 0.1531119 


s: 659 
logit 659 : -0.4571943 
logit mean 659 : -0.4267181 
logit RMSE 659 : 0.06772345 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 659 : -0.5082072 
boosting mean 659 : -0.5059528 
boosting RMSE 659 : 0.1617677 

forest 659 : -0.3918054 
forest mean 659 : -0.3815883 
forest RMSE 659 : 0.05421897 

nnet 659 : -0.4183836 
nnet mean 659 : -0.4298438 
nnet RMSE 659 : 0.1529974 


s: 660 
logit 660 : -0.3866528 
logit mean 660 : -0.4266574 
logit RMSE 660 : 0.06767412 

boosting 660 : -0.4289761 
boosting mean 660 : -0.5058362 
boosting RMSE 660 : 0.161649 

forest 660 : -0.3740434 
forest mean 660 : -0.3815769 
forest RMSE 660 : 0.0541873 

nnet 660 : -0.6138282 
nnet mean 660 : -0.4301225 
nnet RMSE 660 : 0.1531079 


s: 661 
logit 661 : -0.4221199 
logit mean 661 : -0.4266505 
logit RMSE 661 : 0.06762838 

boosting 661 : -0.5041832 
boosting mean 661 : -0.5058337 
boosting RMSE 661 : 0.1615775 

forest 661 : -0.4247518 
forest mean 661 : -0.3816422 
forest RMSE 661 : 0.05415486 

nnet 661 : -0.6551557 
nnet mean 661 : -0.430463 
nnet RMSE 661 : 0.1533136 


s: 662 
logit 662 : -0.4543187 
logit mean 662 : -0.4266923 
logit RMSE 662 : 0.06761025 

boosting 662 : -0.5508876 
boosting mean 662 : -0.5059018 
boosting RMSE 662 : 0.1615619 

forest 662 : -0.3742169 
forest mean 662 : -0.381631 
forest RMSE 662 : 0.05412322 

nnet 662 : -0.3256161 
nnet mean 662 : -0.4303046 
nnet RMSE 662 : 0.153225 


s: 663 
logit 663 : -0.4483664 
logit mean 663 : -0.426725 
logit RMSE 663 : 0.06758535 

boosting 663 : -0.4330399 
boosting mean 663 : -0.5057919 
boosting RMSE 663 : 0.1614451 

forest 663 : -0.4234804 
forest mean 663 : -0.3816941 
forest RMSE 663 : 0.05409007 

nnet 663 : -0.6786541 
nnet mean 663 : -0.4306792 
nnet RMSE 663 : 0.1534914 


s: 664 
logit 664 : -0.3630612 
logit mean 664 : -0.4266291 
logit RMSE 664 : 0.06754965 

boosting 664 : -0.4606657 
boosting mean 664 : -0.5057239 
boosting RMSE 664 : 0.1613406 

forest 664 : -0.3778387 
forest mean 664 : -0.3816883 
forest RMSE 664 : 0.05405617 

nnet 664 : 0.01636877 
nnet mean 664 : -0.4300059 
nnet RMSE 664 : 0.1542245 


s: 665 
logit 665 : -0.3602159 
logit mean 665 : -0.4265292 
logit RMSE 665 : 0.06751647 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 665 : -0.3976309 
boosting mean 665 : -0.5055614 
boosting RMSE 665 : 0.1612193 

forest 665 : -0.3474298 
forest mean 665 : -0.3816368 
forest RMSE 665 : 0.05405396 

nnet 665 : -0.4196055 
nnet mean 665 : -0.4299903 
nnet RMSE 665 : 0.1541104 


s: 666 
logit 666 : -0.3626073 
logit mean 666 : -0.4264333 
logit RMSE 666 : 0.06748132 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 666 : -0.365317 
boosting mean 666 : -0.5053508 
boosting RMSE 666 : 0.1611038 

forest 666 : -0.2741167 
forest mean 666 : -0.3814753 
forest RMSE 666 : 0.05423318 

nnet 666 : -0.4712294 
nnet mean 666 : -0.4300522 
nnet RMSE 666 : 0.1540194 


s: 667 
logit 667 : -0.3695377 
logit mean 667 : -0.4263479 
logit RMSE 667 : 0.06744103 

boosting 667 : -0.4818573 
boosting mean 667 : -0.5053156 
boosting RMSE 667 : 0.1610142 

forest 667 : -0.3862782 
forest mean 667 : -0.3814825 
forest RMSE 667 : 0.05419511 

nnet 667 : -0.2972249 
nnet mean 667 : -0.429853 
nnet RMSE 667 : 0.1539553 


s: 668 
logit 668 : -0.3841963 
logit mean 668 : -0.4262848 
logit RMSE 668 : 0.06739331 

boosting 668 : -0.509637 
boosting mean 668 : -0.505322 
boosting RMSE 668 : 0.1609496 

forest 668 : -0.3939204 
forest mean 668 : -0.3815012 
forest RMSE 668 : 0.05415504 

nnet 668 : -0.6311506 
nnet mean 668 : -0.4301544 
nnet RMSE 668 : 0.1540998 


s: 669 
logit 669 : -0.4658908 
logit mean 669 : -0.4263441 
logit RMSE 669 : 0.06739109 

boosting 669 : -0.6451834 
boosting mean 669 : -0.5055311 
boosting RMSE 669 : 0.1611084 

forest 669 : -0.3589049 
forest mean 669 : -0.3814674 
forest RMSE 669 : 0.05413787 

nnet 669 : -0.7134454 
nnet mean 669 : -0.4305778 
nnet RMSE 669 : 0.1544607 


s: 670 
logit 670 : -0.3927875 
logit mean 670 : -0.426294 
logit RMSE 670 : 0.06734135 

boosting 670 : -0.4662818 
boosting mean 670 : -0.5054725 
boosting RMSE 670 : 0.1610084 

forest 670 : -0.3427242 
forest mean 670 : -0.3814096 
forest RMSE 670 : 0.05414269 

nnet 670 : -0.1416029 
nnet mean 670 : -0.4301465 
nnet RMSE 670 : 0.1546679 


s: 671 
logit 671 : -0.3754424 
logit mean 671 : -0.4262182 
logit RMSE 671 : 0.06729783 

boosting 671 : -0.4873445 
boosting mean 671 : -0.5054455 
boosting RMSE 671 : 0.1609238 

forest 671 : -0.3367475 
forest mean 671 : -0.381343 
forest RMSE 671 : 0.05415741 

nnet 671 : -0.4632883 
nnet mean 671 : -0.4301959 
nnet RMSE 671 : 0.1545719 


s: 672 
logit 672 : -0.3228146 
logit mean 672 : -0.4260643 
logit RMSE 672 : 0.06731363 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 672 : -0.603627 
boosting mean 672 : -0.5055916 
boosting RMSE 672 : 0.1609957 

forest 672 : -0.2854491 
forest mean 672 : -0.3812003 
forest RMSE 672 : 0.05429721 

nnet 672 : -0.0958075 
nnet mean 672 : -0.4296983 
nnet RMSE 672 : 0.1549020 


s: 673 
logit 673 : -0.44583 
logit mean 673 : -0.4260937 
logit RMSE 673 : 0.06728679 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 673 : -0.3874203 
boosting mean 673 : -0.505416 
boosting RMSE 673 : 0.1608768 

forest 673 : -0.4302165 
forest mean 673 : -0.3812731 
forest RMSE 673 : 0.05426936 

nnet 673 : -0.4214193 
nnet mean 673 : -0.429686 
nnet RMSE 673 : 0.1547890 


s: 674 
logit 674 : -0.4433823 
logit mean 674 : -0.4261193 
logit RMSE 674 : 0.06725762 

boosting 674 : -0.3194495 
boosting mean 674 : -0.5051401 
boosting RMSE 674 : 0.1607873 

forest 674 : -0.3774303 
forest mean 674 : -0.3812674 
forest RMSE 674 : 0.05423605 

nnet 674 : -0.402001 
nnet mean 674 : -0.4296449 
nnet RMSE 674 : 0.1546742 


s: 675 
logit 675 : -0.4233557 
logit mean 675 : -0.4261152 
logit RMSE 675 : 0.06721379 

boosting 675 : -0.9299684 
boosting mean 675 : -0.5057695 
boosting RMSE 675 : 0.1619579 

forest 675 : -0.3902053 
forest mean 675 : -0.3812807 
forest RMSE 675 : 0.05419717 

nnet 675 : -0.3351747 
nnet mean 675 : -0.429505 
nnet RMSE 675 : 0.1545797 


s: 676 
logit 676 : -0.4299968 
logit mean 676 : -0.426121 
logit RMSE 676 : 0.06717397 

boosting 676 : -0.5235597 
boosting mean 676 : -0.5057958 
boosting RMSE 676 : 0.1619078 

forest 676 : -0.4674094 
forest mean 676 : -0.3814081 
forest RMSE 676 : 0.05421909 

nnet 676 : -0.4698805 
nnet mean 676 : -0.4295647 
nnet RMSE 676 : 0.1544887 


s: 677 
logit 677 : -0.4819266 
logit mean 677 : -0.4262034 
logit RMSE 677 : 0.06719815 

boosting 677 : -0.4068017 
boosting mean 677 : -0.5056496 
boosting RMSE 677 : 0.1617884 

forest 677 : -0.3480728 
forest mean 677 : -0.3813588 
forest RMSE 677 : 0.05421578 

nnet 677 : -0.4905527 
nnet mean 677 : -0.4296548 
nnet RMSE 677 : 0.1544138 


s: 678 
logit 678 : -0.3362406 
logit mean 678 : -0.4260707 
logit RMSE 678 : 0.0671932 

boosting 678 : -0.5868341 
boosting mean 678 : -0.5057693 
boosting RMSE 678 : 0.1618282 

forest 678 : -0.2866785 
forest mean 678 : -0.3812192 
forest RMSE 678 : 0.05435031 

nnet 678 : -0.4908974 
nnet mean 678 : -0.4297451 
nnet RMSE 678 : 0.1543394 


s: 679 
logit 679 : -0.3875752 
logit mean 679 : -0.426014 
logit RMSE 679 : 0.0671454 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 679 : -0.6651574 
boosting mean 679 : -0.506004 
boosting RMSE 679 : 0.1620289 

forest 679 : -0.3992369 
forest mean 679 : -0.3812457 
forest RMSE 679 : 0.05431028 

nnet 679 : -0.1903646 
nnet mean 679 : -0.4293926 
nnet RMSE 679 : 0.1544354 


s: 680 
logit 680 : -0.4419357 
logit mean 680 : -0.4260374 
logit RMSE 680 : 0.06711528 

boosting 680 : -0.4347236 
boosting mean 680 : -0.5058992 
boosting RMSE 680 : 0.1619152 

forest 680 : -0.3570367 
forest mean 680 : -0.3812101 
forest RMSE 680 : 0.05429533 

nnet 680 : -0.862713 
nnet mean 680 : -0.4300298 
nnet RMSE 680 : 0.1553386 


s: 681 
logit 681 : -0.341319 
logit mean 681 : -0.425913 
logit RMSE 681 : 0.06710367 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 681 : -0.3669078 
boosting mean 681 : -0.5056951 
boosting RMSE 681 : 0.1618012 

forest 681 : -0.4237099 
forest mean 681 : -0.3812725 
forest RMSE 681 : 0.05426306 

nnet 681 : -0.4245886 
nnet mean 681 : -0.4300218 
nnet RMSE 681 : 0.1552273 


s: 682 
logit 682 : -0.390447 
logit mean 682 : -0.425861 
logit RMSE 682 : 0.06705546 

boosting 682 : -0.5950572 
boosting mean 682 : -0.5058262 
boosting RMSE 682 : 0.1618550 

forest 682 : -0.3297269 
forest mean 682 : -0.3811969 
forest RMSE 682 : 0.05428999 

nnet 682 : -0.6414405 
nnet mean 682 : -0.4303318 
nnet RMSE 682 : 0.1553888 


s: 683 
logit 683 : -0.3584832 
logit mean 683 : -0.4257624 
logit RMSE 683 : 0.06702518 

boosting 683 : -0.4584342 
boosting mean 683 : -0.5057568 
boosting RMSE 683 : 0.1617519 

forest 683 : -0.4010351 
forest mean 683 : -0.381226 
forest RMSE 683 : 0.05425025 

nnet 683 : -0.5957332 
nnet mean 683 : -0.430574 
nnet RMSE 683 : 0.1554555 


s: 684 
logit 684 : -0.4040538 
logit mean 684 : -0.4257306 
logit RMSE 684 : 0.06697634 

boosting 684 : -0.7741793 
boosting mean 684 : -0.5061492 
boosting RMSE 684 : 0.1622656 

forest 684 : -0.3393906 
forest mean 684 : -0.3811648 
forest RMSE 684 : 0.05426009 

nnet 684 : -0.5225813 
nnet mean 684 : -0.4307085 
nnet RMSE 684 : 0.1554125 


s: 685 
logit 685 : -0.441338 
logit mean 685 : -0.4257534 
logit RMSE 685 : 0.06694607 

boosting 685 : -0.5511049 
boosting mean 685 : -0.5062148 
boosting RMSE 685 : 0.1622498 

forest 685 : -0.3364682 
forest mean 685 : -0.3810996 
forest RMSE 685 : 0.05427478 

nnet 685 : -0.3914862 
nnet mean 685 : -0.4306513 
nnet RMSE 685 : 0.1552994 


s: 686 
logit 686 : -0.3059811 
logit mean 686 : -0.4255788 
logit RMSE 686 : 0.0669935 

boosting 686 : -0.5239837 
boosting mean 686 : -0.5062407 
boosting RMSE 686 : 0.1622006 

forest 686 : -0.3673782 
forest mean 686 : -0.3810796 
forest RMSE 686 : 0.05424951 

nnet 686 : -0.2151769 
nnet mean 686 : -0.4303371 
nnet RMSE 686 : 0.1553465 


s: 687 
logit 687 : -0.4140785 
logit mean 687 : -0.4255621 
logit RMSE 687 : 0.06694688 

boosting 687 : -0.4892889 
boosting mean 687 : -0.5062161 
boosting RMSE 687 : 0.1621183 

forest 687 : -0.3739818 
forest mean 687 : -0.3810692 
forest RMSE 687 : 0.0542191 

nnet 687 : -0.4360781 
nnet mean 687 : -0.4303455 
nnet RMSE 687 : 0.1552395 


s: 688 
logit 688 : -0.4698817 
logit mean 688 : -0.4256265 
logit RMSE 688 : 0.06695124 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 688 : -0.6441973 
boosting mean 688 : -0.5064166 
boosting RMSE 688 : 0.1622678 

forest 688 : -0.4353140 
forest mean 688 : -0.3811481 
forest RMSE 688 : 0.0541964 

nnet 688 : -0.2133768 
nnet mean 688 : -0.4300301 
nnet RMSE 688 : 0.1552897 


s: 689 
logit 689 : -0.4756155 
logit mean 689 : -0.4256991 
logit RMSE 689 : 0.06696463 

boosting 689 : -0.7202887 
boosting mean 689 : -0.506727 
boosting RMSE 689 : 0.1626084 

forest 689 : -0.3593272 
forest mean 689 : -0.3811164 
forest RMSE 689 : 0.05417922 

nnet 689 : -0.5462852 
nnet mean 689 : -0.4301989 
nnet RMSE 689 : 0.155277 


s: 690 
logit 690 : -0.4694109 
logit mean 690 : -0.4257624 
logit RMSE 690 : 0.06696824 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 690 : -0.4975704 
boosting mean 690 : -0.5067137 
boosting RMSE 690 : 0.162533 

forest 690 : -0.3743984 
forest mean 690 : -0.3811067 
forest RMSE 690 : 0.05414872 

nnet 690 : -0.3104583 
nnet mean 690 : -0.4300253 
nnet RMSE 690 : 0.1552019 


s: 691 
logit 691 : -0.3734164 
logit mean 691 : -0.4256867 
logit RMSE 691 : 0.0669274 

boosting 691 : -0.5164933 
boosting mean 691 : -0.5067279 
boosting RMSE 691 : 0.1624758 

forest 691 : -0.3714825 
forest mean 691 : -0.3810928 
forest RMSE 691 : 0.0541204 

nnet 691 : -0.5879078 
nnet mean 691 : -0.4302538 
nnet RMSE 691 : 0.1552542 


s: 692 
logit 692 : -0.4017227 
logit mean 692 : -0.425652 
logit RMSE 692 : 0.06687906 

boosting 692 : -0.5585433 
boosting mean 692 : -0.5068028 
boosting RMSE 692 : 0.1624702 

forest 692 : -0.437189 
forest mean 692 : -0.3811738 
forest RMSE 692 : 0.05409976 

nnet 692 : -0.5272874 
nnet mean 692 : -0.430394 
nnet RMSE 692 : 0.1552174 


s: 693 
logit 693 : -0.4722903 
logit mean 693 : -0.4257193 
logit RMSE 693 : 0.06688718 

boosting 693 : -0.4823598 
boosting mean 693 : -0.5067675 
boosting RMSE 693 : 0.1623831 

forest 693 : -0.427345 
forest mean 693 : -0.3812404 
forest RMSE 693 : 0.05407069 

nnet 693 : -0.4374244 
nnet mean 693 : -0.4304042 
nnet RMSE 693 : 0.1551119 


s: 694 
logit 694 : -0.495637 
logit mean 694 : -0.4258201 
logit RMSE 694 : 0.06693749 

boosting 694 : -0.5497529 
boosting mean 694 : -0.5068294 
boosting RMSE 694 : 0.1623656 

forest 694 : -0.4038488 
forest mean 694 : -0.381273 
forest RMSE 694 : 0.05403191 

nnet 694 : -0.3920354 
nnet mean 694 : -0.4303489 
nnet RMSE 694 : 0.1550004 


s: 695 
logit 695 : -0.4241057 
logit mean 695 : -0.4258176 
logit RMSE 695 : 0.06689557 

boosting 695 : -0.3071452 
boosting mean 695 : -0.5065421 
boosting RMSE 695 : 0.1622869 

forest 695 : -0.4101208 
forest mean 695 : -0.3813145 
forest RMSE 695 : 0.05399439 

nnet 695 : -0.6634611 
nnet mean 695 : -0.4306843 
nnet RMSE 695 : 0.1552109 


s: 696 
logit 696 : -0.4644669 
logit mean 696 : -0.4258731 
logit RMSE 696 : 0.06689214 

boosting 696 : -0.5338875 
boosting mean 696 : -0.5065814 
boosting RMSE 696 : 0.1622497 

forest 696 : -0.4343314 
forest mean 696 : -0.3813907 
forest RMSE 696 : 0.05397128 

nnet 696 : -0.3791512 
nnet mean 696 : -0.4306103 
nnet RMSE 696 : 0.1551014 


s: 697 
logit 697 : -0.4777813 
logit mean 697 : -0.4259476 
logit RMSE 697 : 0.06690903 

boosting 697 : -0.4995209 
boosting mean 697 : -0.5065713 
boosting RMSE 697 : 0.1621771 

forest 697 : -0.3829118 
forest mean 697 : -0.3813929 
forest RMSE 697 : 0.05393643 

nnet 697 : -0.5029265 
nnet mean 697 : -0.430714 
nnet RMSE 697 : 0.1550391 


s: 698 
logit 698 : -0.4168403 
logit mean 698 : -0.4259346 
logit RMSE 698 : 0.06686413 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 698 : -0.5448227 
boosting mean 698 : -0.5066261 
boosting RMSE 698 : 0.1621536 

forest 698 : -0.4061563 
forest mean 698 : -0.3814284 
forest RMSE 698 : 0.05389829 

nnet 698 : -0.589594 
nnet mean 698 : -0.4309416 
nnet RMSE 698 : 0.1550941 


s: 699 
logit 699 : -0.3378538 
logit mean 699 : -0.4258086 
logit RMSE 699 : 0.06685761 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 699 : -0.5085986 
boosting mean 699 : -0.5066289 
boosting RMSE 699 : 0.1620896 

forest 699 : -0.3511175 
forest mean 699 : -0.381385 
forest RMSE 699 : 0.05389145 

nnet 699 : -0.3644668 
nnet mean 699 : -0.4308465 
nnet RMSE 699 : 0.1549890 


s: 700 
logit 700 : -0.4733085 
logit mean 700 : -0.4258764 
logit RMSE 700 : 0.06686727 

boosting 700 : -0.5626267 
boosting mean 700 : -0.5067089 
boosting RMSE 700 : 0.1620903 

forest 700 : -0.3517380 
forest mean 700 : -0.3813426 
forest RMSE 700 : 0.05388382 

nnet 700 : -0.0930358 
nnet mean 700 : -0.430364 
nnet RMSE 700 : 0.1553122 


s: 701 
logit 701 : -0.4658933 
logit mean 701 : -0.4259335 
logit RMSE 701 : 0.0668659 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 701 : -0.4778578 
boosting mean 701 : -0.5066678 
boosting RMSE 701 : 0.1620014 

forest 701 : -0.3016415 
forest mean 701 : -0.3812290 
forest RMSE 701 : 0.05397338 

nnet 701 : -0.03659661 
nnet mean 701 : -0.4298022 
nnet RMSE 701 : 0.1558071 


s: 702 
logit 702 : -0.4780857 
logit mean 702 : -0.4260078 
logit RMSE 702 : 0.06688322 

boosting 702 : -0.6197082 
boosting mean 702 : -0.5068288 
boosting RMSE 702 : 0.1620982 

forest 702 : -0.4786457 
forest mean 702 : -0.3813677 
forest RMSE 702 : 0.05401654 

nnet 702 : -0.5791297 
nnet mean 702 : -0.4300150 
nnet RMSE 702 : 0.1558428 


s: 703 
logit 703 : -0.6205483 
logit mean 703 : -0.4262845 
logit RMSE 703 : 0.06735126 

boosting 703 : -0.5789114 
boosting mean 703 : -0.5069313 
boosting RMSE 703 : 0.1621234 

forest 703 : -0.4603356 
forest mean 703 : -0.3814801 
forest RMSE 703 : 0.05402605 

nnet 703 : -0.2644883 
nnet mean 703 : -0.4297795 
nnet RMSE 703 : 0.1558158 


s: 704 
logit 704 : -0.4755069 
logit mean 704 : -0.4263544 
logit RMSE 704 : 0.06736355 

boosting 704 : -0.5082209 
boosting mean 704 : -0.5069331 
boosting RMSE 704 : 0.1620595 

forest 704 : -0.4527785 
forest mean 704 : -0.3815813 
forest RMSE 704 : 0.0540243 

nnet 704 : -0.5293572 
nnet mean 704 : -0.4299209 
nnet RMSE 704 : 0.1557814 


s: 705 
logit 705 : -0.4755162 
logit mean 705 : -0.4264242 
logit RMSE 705 : 0.06737581 

boosting 705 : -0.5779085 
boosting mean 705 : -0.5070338 
boosting RMSE 705 : 0.1620831 

forest 705 : -0.3464248 
forest mean 705 : -0.3815315 
forest RMSE 705 : 0.05402366 

nnet 705 : -0.585946 
nnet mean 705 : -0.4301423 
nnet RMSE 705 : 0.1558283 


s: 706 
logit 706 : -0.3322758 
logit mean 706 : -0.4262908 
logit RMSE 706 : 0.0673763 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 706 : -0.3666935 
boosting mean 706 : -0.506835 
boosting RMSE 706 : 0.1619731 

forest 706 : -0.3140337 
forest mean 706 : -0.3814359 
forest RMSE 706 : 0.05408225 

nnet 706 : -0.4249512 
nnet mean 706 : -0.4301349 
nnet RMSE 706 : 0.1557207 


s: 707 
logit 707 : -0.3309558 
logit mean 707 : -0.426156 
logit RMSE 707 : 0.0673787 

boosting 707 : -0.2399441 
boosting mean 707 : -0.5064575 
boosting RMSE 707 : 0.1619704 

forest 707 : -0.2712522 
forest mean 707 : -0.38128 
forest RMSE 707 : 0.05426047 

nnet 707 : -0.4263061 
nnet mean 707 : -0.4301295 
nnet RMSE 707 : 0.1556137 


s: 708 
logit 708 : -0.4073223 
logit mean 708 : -0.4261294 
logit RMSE 708 : 0.06733166 

boosting 708 : -0.2847298 
boosting mean 708 : -0.5061444 
boosting RMSE 708 : 0.1619139 

forest 708 : -0.3407902 
forest mean 708 : -0.3812228 
forest RMSE 708 : 0.05426778 

nnet 708 : -0.1607305 
nnet mean 708 : -0.429749 
nnet RMSE 708 : 0.1557636 


s: 709 
logit 709 : -0.4001447 
logit mean 709 : -0.4260927 
logit RMSE 709 : 0.06728416 

boosting 709 : -0.5127807 
boosting mean 709 : -0.5061537 
boosting RMSE 709 : 0.1618552 

forest 709 : -0.3638208 
forest mean 709 : -0.3811983 
forest RMSE 709 : 0.05424651 

nnet 709 : -0.4350814 
nnet mean 709 : -0.4297565 
nnet RMSE 709 : 0.1556592 


s: 710 
logit 710 : -0.3750005 
logit mean 710 : -0.4260208 
logit RMSE 710 : 0.0672433 

boosting 710 : -0.3792377 
boosting mean 710 : -0.505975 
boosting RMSE 710 : 0.161743 

forest 710 : -0.3665903 
forest mean 710 : -0.3811777 
forest RMSE 710 : 0.0542228 

nnet 710 : -0.4066873 
nnet mean 710 : -0.429724 
nnet RMSE 710 : 0.1555498 


s: 711 
logit 711 : -0.4318944 
logit mean 711 : -0.426029 
logit RMSE 711 : 0.06720664 

boosting 711 : -0.7349349 
boosting mean 711 : -0.506297 
boosting RMSE 711 : 0.1621166 

forest 711 : -0.3835791 
forest mean 711 : -0.3811811 
forest RMSE 711 : 0.05418815 

nnet 711 : -0.6835377 
nnet mean 711 : -0.430081 
nnet RMSE 711 : 0.1558037 


s: 712 
logit 712 : -0.4709154 
logit mean 712 : -0.4260921 
logit RMSE 712 : 0.067212 

boosting 712 : -0.5030831 
boosting mean 712 : -0.5062925 
boosting RMSE 712 : 0.1620487 

forest 712 : -0.3807836 
forest mean 712 : -0.3811805 
forest RMSE 712 : 0.05415487 

nnet 712 : -0.4949964 
nnet mean 712 : -0.4301722 
nnet RMSE 712 : 0.1557349 


s: 713 
logit 713 : -0.3506667 
logit mean 713 : -0.4259863 
logit RMSE 713 : 0.06719025 

boosting 713 : -0.40013 
boosting mean 713 : -0.5061436 
boosting RMSE 713 : 0.1619351 

forest 713 : -0.3352158 
forest mean 713 : -0.3811161 
forest RMSE 713 : 0.05417124 

nnet 713 : -0.04345351 
nnet mean 713 : -0.4296298 
nnet RMSE 713 : 0.1561974 


s: 714 
logit 714 : -0.4610183 
logit mean 714 : -0.4260353 
logit RMSE 714 : 0.067182 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 714 : -0.537145 
boosting mean 714 : -0.506187 
boosting RMSE 714 : 0.161903 

forest 714 : -0.3215953 
forest mean 714 : -0.3810327 
forest RMSE 714 : 0.05421276 

nnet 714 : -0.4463575 
nnet mean 714 : -0.4296532 
nnet RMSE 714 : 0.1560977 


s: 715 
logit 715 : -0.4093842 
logit mean 715 : -0.4260121 
logit RMSE 715 : 0.06713592 

boosting 715 : -0.4282975 
boosting mean 715 : -0.5060781 
boosting RMSE 715 : 0.1617932 

forest 715 : -0.3400209 
forest mean 715 : -0.3809753 
forest RMSE 715 : 0.05422125 

nnet 715 : -0.2911555 
nnet mean 715 : -0.4294595 
nnet RMSE 715 : 0.1560416 


s: 716 
logit 716 : -0.4851226 
logit mean 716 : -0.4260946 
logit RMSE 716 : 0.0671644 

boosting 716 : -0.4673059 
boosting mean 716 : -0.5060239 
boosting RMSE 716 : 0.1616997 

forest 716 : -0.2864544 
forest mean 716 : -0.3808433 
forest RMSE 716 : 0.05434928 

nnet 716 : -0.5079616 
nnet mean 716 : -0.4295691 
nnet RMSE 716 : 0.1559848 


s: 717 
logit 717 : -0.4134823 
logit mean 717 : -0.426077 
logit RMSE 717 : 0.06711944 

boosting 717 : -0.4842614 
boosting mean 717 : -0.5059936 
boosting RMSE 717 : 0.1616176 

forest 717 : -0.4721538 
forest mean 717 : -0.3809707 
forest RMSE 717 : 0.05437817 

nnet 717 : -0.3229935 
nnet mean 717 : -0.4294205 
nnet RMSE 717 : 0.1559025 


s: 718 
logit 718 : -0.333763 
logit mean 718 : -0.4259484 
logit RMSE 718 : 0.06711822 

boosting 718 : -0.3706032 
boosting mean 718 : -0.505805 
boosting RMSE 718 : 0.1615087 

forest 718 : -0.344399 
forest mean 718 : -0.3809197 
forest RMSE 718 : 0.0543799 

nnet 718 : -0.3373244 
nnet mean 718 : -0.4292922 
nnet RMSE 718 : 0.1558114 


s: 719 
logit 719 : -0.4809439 
logit mean 719 : -0.4260249 
logit RMSE 719 : 0.06713942 

boosting 719 : -0.6427915 
boosting mean 719 : -0.5059955 
boosting RMSE 719 : 0.1616502 

forest 719 : -0.4160353 
forest mean 719 : -0.3809686 
forest RMSE 719 : 0.05434536 

nnet 719 : -0.542239 
nnet mean 719 : -0.4294493 
nnet RMSE 719 : 0.1557934 


s: 720 
logit 720 : -0.4247148 
logit mean 720 : -0.4260231 
logit RMSE 720 : 0.0670991 

boosting 720 : -0.3853913 
boosting mean 720 : -0.505828 
boosting RMSE 720 : 0.1615388 

forest 720 : -0.4291583 
forest mean 720 : -0.3810355 
forest RMSE 720 : 0.05431847 

nnet 720 : -0.4685818 
nnet mean 720 : -0.4295037 
nnet RMSE 720 : 0.1557061 


s: 721 
logit 721 : -0.4486956 
logit mean 721 : -0.4260546 
logit RMSE 721 : 0.06707708 

boosting 721 : -0.5923649 
boosting mean 721 : -0.505948 
boosting RMSE 721 : 0.1615856 

forest 721 : -0.5111139 
forest mean 721 : -0.3812159 
forest RMSE 721 : 0.0544383 

nnet 721 : -0.633515 
nnet mean 721 : -0.4297866 
nnet RMSE 721 : 0.1558409 


s: 722 
logit 722 : -0.4364461 
logit mean 722 : -0.4260690 
logit RMSE 722 : 0.06704433 

boosting 722 : -0.5366312 
boosting mean 722 : -0.5059905 
boosting RMSE 722 : 0.1615537 

forest 722 : -0.3170877 
forest mean 722 : -0.3811271 
forest RMSE 722 : 0.05448803 

nnet 722 : -0.2216955 
nnet mean 722 : -0.4294984 
nnet RMSE 722 : 0.1558743 


s: 723 
logit 723 : -0.4283282 
logit mean 723 : -0.4260721 
logit RMSE 723 : 0.06700623 

boosting 723 : -0.6135422 
boosting mean 723 : -0.5061393 
boosting RMSE 723 : 0.1616372 

forest 723 : -0.3516695 
forest mean 723 : -0.3810864 
forest RMSE 723 : 0.05447999 

nnet 723 : -0.4634911 
nnet mean 723 : -0.4295454 
nnet RMSE 723 : 0.1557843 


s: 724 
logit 724 : -0.3230681 
logit mean 724 : -0.4259298 
logit RMSE 724 : 0.06702096 

boosting 724 : -0.4348063 
boosting mean 724 : -0.5060408 
boosting RMSE 724 : 0.1615307 

forest 724 : -0.381649 
forest mean 724 : -0.3810871 
forest RMSE 724 : 0.05444663 

nnet 724 : -0.417329 
nnet mean 724 : -0.4295286 
nnet RMSE 724 : 0.1556781 


s: 725 
logit 725 : -0.5807857 
logit mean 725 : -0.4261434 
logit RMSE 725 : 0.06731043 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 725 : -0.535053 
boosting mean 725 : -0.5060808 
boosting RMSE 725 : 0.1614971 

forest 725 : -0.3907047 
forest mean 725 : -0.3811004 
forest RMSE 725 : 0.05441016 

nnet 725 : -0.5257863 
nnet mean 725 : -0.4296613 
nnet RMSE 725 : 0.1556408 


s: 726 
logit 726 : -0.3738995 
logit mean 726 : -0.4260714 
logit RMSE 726 : 0.06727103 

boosting 726 : -0.5673604 
boosting mean 726 : -0.5061652 
boosting RMSE 726 : 0.1615054 

forest 726 : -0.3678812 
forest mean 726 : -0.3810822 
forest RMSE 726 : 0.05438574 

nnet 726 : -0.3326632 
nnet mean 726 : -0.4295277 
nnet RMSE 726 : 0.1555536 


s: 727 
logit 727 : -0.42149 
logit mean 727 : -0.4260651 
logit RMSE 727 : 0.06722947 

boosting 727 : -0.531446 
boosting mean 727 : -0.5062 
boosting RMSE 727 : 0.1614679 

forest 727 : -0.5515463 
forest mean 727 : -0.3813167 
forest RMSE 727 : 0.05463818 

nnet 727 : -0.4535187 
nnet mean 727 : -0.4295607 
nnet RMSE 727 : 0.1554593 


s: 728 
logit 728 : -0.3630696 
logit mean 728 : -0.4259786 
logit RMSE 728 : 0.06719722 

boosting 728 : -0.3928901 
boosting mean 728 : -0.5060443 
boosting RMSE 728 : 0.1613571 

forest 728 : -0.3574518 
forest mean 728 : -0.3812839 
forest RMSE 728 : 0.05462341 

nnet 728 : -0.1955209 
nnet mean 728 : -0.4292392 
nnet RMSE 728 : 0.1555372 


s: 729 
logit 729 : -0.4395799 
logit mean 729 : -0.4259973 
logit RMSE 729 : 0.06716712 

boosting 729 : -0.6349848 
boosting mean 729 : -0.5062212 
boosting RMSE 729 : 0.1614811 

forest 729 : -0.4235907 
forest mean 729 : -0.3813419 
forest RMSE 729 : 0.05459292 

nnet 729 : -0.3269361 
nnet mean 729 : -0.4290989 
nnet RMSE 729 : 0.1554541 


s: 730 
logit 730 : -0.3191457 
logit mean 730 : -0.4258509 
logit RMSE 730 : 0.06718777 

boosting 730 : -0.5490919 
boosting mean 730 : -0.5062799 
boosting RMSE 730 : 0.1614648 

forest 730 : -0.3800585 
forest mean 730 : -0.3813402 
forest RMSE 730 : 0.05456051 

nnet 730 : -0.3762523 
nnet mean 730 : -0.4290265 
nnet RMSE 730 : 0.1553500 


s: 731 
logit 731 : -0.4361138 
logit mean 731 : -0.4258649 
logit RMSE 731 : 0.06715509 

boosting 731 : -0.5730452 
boosting mean 731 : -0.5063713 
boosting RMSE 731 : 0.1614812 

forest 731 : -0.3584137 
forest mean 731 : -0.3813088 
forest RMSE 731 : 0.05454487 

nnet 731 : -0.5200826 
nnet mean 731 : -0.4291511 
nnet RMSE 731 : 0.1553073 


s: 732 
logit 732 : -0.5124915 
logit mean 732 : -0.4259833 
logit RMSE 732 : 0.06723788 

boosting 732 : -0.5104019 
boosting mean 732 : -0.5063768 
boosting RMSE 732 : 0.1614225 

forest 732 : -0.3682944 
forest mean 732 : -0.381291 
forest RMSE 732 : 0.05452019 

nnet 732 : -0.4178404 
nnet mean 732 : -0.4291356 
nnet RMSE 732 : 0.1552025 


s: 733 
logit 733 : -0.4719552 
logit mean 733 : -0.426046 
logit RMSE 733 : 0.06724454 

boosting 733 : -0.4142737 
boosting mean 733 : -0.5062511 
boosting RMSE 733 : 0.1613132 

forest 733 : -0.3558057 
forest mean 733 : -0.3812562 
forest RMSE 733 : 0.05450744 

nnet 733 : -0.4595271 
nnet mean 733 : -0.4291771 
nnet RMSE 733 : 0.1551122 


s: 734 
logit 734 : -0.3872591 
logit mean 734 : -0.4259931 
logit RMSE 734 : 0.06720036 

boosting 734 : -0.5423517 
boosting mean 734 : -0.5063003 
boosting RMSE 734 : 0.1612889 

forest 734 : -0.3751307 
forest mean 734 : -0.3812479 
forest RMSE 734 : 0.05447803 

nnet 734 : -0.4436225 
nnet mean 734 : -0.4291968 
nnet RMSE 734 : 0.1550149 


s: 735 
logit 735 : -0.4634263 
logit mean 735 : -0.4260441 
logit RMSE 735 : 0.06719537 

boosting 735 : -0.4372082 
boosting mean 735 : -0.5062063 
boosting RMSE 735 : 0.1611850 

forest 735 : -0.3321302 
forest mean 735 : -0.3811811 
forest RMSE 735 : 0.05449849 

nnet 735 : -0.3050102 
nnet mean 735 : -0.4290278 
nnet RMSE 735 : 0.154949 


s: 736 
logit 736 : -0.4075986 
logit mean 736 : -0.426019 
logit RMSE 736 : 0.06715029 

boosting 736 : -0.2909286 
boosting mean 736 : -0.5059138 
boosting RMSE 736 : 0.1611256 

forest 736 : -0.4397989 
forest mean 736 : -0.3812607 
forest RMSE 736 : 0.0544812 

nnet 736 : -0.3787757 
nnet mean 736 : -0.4289595 
nnet RMSE 736 : 0.1548457 


s: 737 
logit 737 : -0.3430838 
logit mean 737 : -0.4259065 
logit RMSE 737 : 0.06713746 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 737 : -0.6176825 
boosting mean 737 : -0.5060654 
boosting RMSE 737 : 0.1612158 

forest 737 : -0.4348124 
forest mean 737 : -0.3813334 
forest RMSE 737 : 0.05445933 

nnet 737 : -0.3282923 
nnet mean 737 : -0.4288229 
nnet RMSE 737 : 0.1547631 


s: 738 
logit 738 : -0.48748 
logit mean 738 : -0.4259899 
logit RMSE 738 : 0.06716919 

boosting 738 : -0.4473745 
boosting mean 738 : -0.5059859 
boosting RMSE 738 : 0.1611159 

forest 738 : -0.4191381 
forest mean 738 : -0.3813846 
forest RMSE 738 : 0.05442698 

nnet 738 : -0.1396698 
nnet mean 738 : -0.4284311 
nnet RMSE 738 : 0.1549549 


s: 739 
logit 739 : -0.3574567 
logit mean 739 : -0.4258972 
logit RMSE 739 : 0.06714197 

boosting 739 : -0.4750774 
boosting mean 739 : -0.5059441 
boosting RMSE 739 : 0.1610306 

forest 739 : -0.3226161 
forest mean 739 : -0.3813051 
forest RMSE 739 : 0.05446458 

nnet 739 : -0.5319828 
nnet mean 739 : -0.4285713 
nnet RMSE 739 : 0.1549261 


s: 740 
logit 740 : -0.4828712 
logit mean 740 : -0.4259742 
logit RMSE 740 : 0.06716571 

boosting 740 : -0.4365048 
boosting mean 740 : -0.5058503 
boosting RMSE 740 : 0.1609273 

forest 740 : -0.413854 
forest mean 740 : -0.3813491 
forest RMSE 740 : 0.05443015 

nnet 740 : -0.3901187 
nnet mean 740 : -0.4285193 
nnet RMSE 740 : 0.1548218 


s: 741 
logit 741 : -0.4331108 
logit mean 741 : -0.4259838 
logit RMSE 741 : 0.0671314 

boosting 741 : -0.5460843 
boosting mean 741 : -0.5059046 
boosting RMSE 741 : 0.1609082 

forest 741 : -0.3814976 
forest mean 741 : -0.3813493 
forest RMSE 741 : 0.05439766 

nnet 741 : -0.2875691 
nnet mean 741 : -0.4283291 
nnet RMSE 741 : 0.1547724 


s: 742 
logit 742 : -0.3094297 
logit mean 742 : -0.4258267 
logit RMSE 742 : 0.06716849 

boosting 742 : -0.260379 
boosting mean 742 : -0.5055737 
boosting RMSE 742 : 0.1608814 

forest 742 : -0.3781617 
forest mean 742 : -0.381345 
forest RMSE 742 : 0.0543669 

nnet 742 : -0.5348368 
nnet mean 742 : -0.4284726 
nnet RMSE 742 : 0.1547473 


s: 743 
logit 743 : -0.526302 
logit mean 743 : -0.4259620 
logit RMSE 743 : 0.06728301 

boosting 743 : -0.4974326 
boosting mean 743 : -0.5055627 
boosting RMSE 743 : 0.1608129 

forest 743 : -0.4693701 
forest mean 743 : -0.3814634 
forest RMSE 743 : 0.05438988 

nnet 743 : -0.6991412 
nnet mean 743 : -0.4288369 
nnet RMSE 743 : 0.155032 


s: 744 
logit 744 : -0.4088274 
logit mean 744 : -0.4259389 
logit RMSE 744 : 0.06723856 

boosting 744 : -0.5528366 
boosting mean 744 : -0.5056262 
boosting RMSE 744 : 0.1608024 

forest 744 : -0.3780226 
forest mean 744 : -0.3814588 
forest RMSE 744 : 0.05435928 

nnet 744 : -0.4908352 
nnet mean 744 : -0.4289202 
nnet RMSE 744 : 0.1549636 


s: 745 
logit 745 : -0.4263904 
logit mean 745 : -0.4259395 
logit RMSE 745 : 0.06720038 

boosting 745 : -0.5123505 
boosting mean 745 : -0.5056353 
boosting RMSE 745 : 0.1607472 

forest 745 : -0.3230690 
forest mean 745 : -0.3813804 
forest RMSE 745 : 0.05439586 

nnet 745 : -0.6351364 
nnet mean 745 : -0.429197 
nnet RMSE 745 : 0.1550990 


s: 746 
logit 746 : -0.4319945 
logit mean 746 : -0.4259476 
logit RMSE 746 : 0.06716554 

boosting 746 : -0.467962 
boosting mean 746 : -0.5055848 
boosting RMSE 746 : 0.1606587 

forest 746 : -0.3450648 
forest mean 746 : -0.3813318 
forest RMSE 746 : 0.05439659 

nnet 746 : -0.4625162 
nnet mean 746 : -0.4292417 
nnet RMSE 746 : 0.1550119 


s: 747 
logit 747 : -0.4287684 
logit mean 747 : -0.4259514 
logit RMSE 747 : 0.06712882 

boosting 747 : -0.4693629 
boosting mean 747 : -0.5055363 
boosting RMSE 747 : 0.1605711 

forest 747 : -0.3897362 
forest mean 747 : -0.381343 
forest RMSE 747 : 0.05436146 

nnet 747 : -0.4092974 
nnet mean 747 : -0.429215 
nnet RMSE 747 : 0.1549085 


s: 748 
logit 748 : -0.4370331 
logit mean 748 : -0.4259662 
logit RMSE 748 : 0.0670976 

boosting 748 : -0.4339381 
boosting mean 748 : -0.5054406 
boosting RMSE 748 : 0.1604686 

forest 748 : -0.388184 
forest mean 748 : -0.3813522 
forest RMSE 748 : 0.05432683 

nnet 748 : -0.1569866 
nnet mean 748 : -0.4288511 
nnet RMSE 748 : 0.1550597 


s: 749 
logit 749 : -0.5249356 
logit mean 749 : -0.4260984 
logit RMSE 749 : 0.067208 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 749 : -0.4518328 
boosting mean 749 : -0.505369 
boosting RMSE 749 : 0.1603726 

forest 749 : -0.3274054 
forest mean 749 : -0.3812801 
forest RMSE 749 : 0.05435531 

nnet 749 : -0.4245746 
nnet mean 749 : -0.4288454 
nnet RMSE 749 : 0.1549587 


s: 750 
logit 750 : -0.2981464 
logit mean 750 : -0.4259278 
logit RMSE 750 : 0.06726608 

boosting 750 : -0.8534595 
boosting mean 750 : -0.5058331 
boosting RMSE 750 : 0.1611187 

forest 750 : -0.3472019 
forest mean 750 : -0.3812347 
forest RMSE 750 : 0.05435326 

nnet 750 : -0.7822366 
nnet mean 750 : -0.4293165 
nnet RMSE 750 : 0.1554831 


s: 751 
logit 751 : -0.4538134 
logit mean 751 : -0.4259649 
logit RMSE 751 : 0.06724996 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 751 : -0.4006306 
boosting mean 751 : -0.505693 
boosting RMSE 751 : 0.1610114 

forest 751 : -0.4196968 
forest mean 751 : -0.3812859 
forest RMSE 751 : 0.05432182 

nnet 751 : -0.612385 
nnet mean 751 : -0.4295603 
nnet RMSE 751 : 0.1555727 


s: 752 
logit 752 : -0.4443998 
logit mean 752 : -0.4259894 
logit RMSE 752 : 0.06722473 

boosting 752 : -0.4973522 
boosting mean 752 : -0.5056819 
boosting RMSE 752 : 0.1609435 

forest 752 : -0.40396 
forest mean 752 : -0.3813161 
forest RMSE 752 : 0.05428588 

nnet 752 : -0.431682 
nnet mean 752 : -0.4295631 
nnet RMSE 752 : 0.1554735 


s: 753 
logit 753 : -0.3052555 
logit mean 753 : -0.4258291 
logit RMSE 753 : 0.06726874 

boosting 753 : -0.5599133 
boosting mean 753 : -0.505754 
boosting RMSE 753 : 0.1609421 

forest 753 : -0.3475046 
forest mean 753 : -0.3812712 
forest RMSE 753 : 0.05428354 

nnet 753 : -0.4280383 
nnet mean 753 : -0.4295611 
nnet RMSE 753 : 0.1553736 


s: 754 
logit 754 : -0.3486063 
logit mean 754 : -0.4257267 
logit RMSE 754 : 0.06725017 

boosting 754 : -0.3147665 
boosting mean 754 : -0.5055007 
boosting RMSE 754 : 0.1608653 

forest 754 : -0.3619836 
forest mean 754 : -0.3812456 
forest RMSE 754 : 0.0542652 

nnet 754 : -0.6199592 
nnet mean 754 : -0.4298136 
nnet RMSE 754 : 0.1554770 


s: 755 
logit 755 : -0.4315151 
logit mean 755 : -0.4257343 
logit RMSE 755 : 0.0672154 

boosting 755 : -0.6281053 
boosting mean 755 : -0.505663 
boosting RMSE 755 : 0.1609730 

forest 755 : -0.348163 
forest mean 755 : -0.3812018 
forest RMSE 755 : 0.05426205 

nnet 755 : -0.3733379 
nnet mean 755 : -0.4297388 
nnet RMSE 755 : 0.1553771 


s: 756 
logit 756 : -0.4711671 
logit mean 756 : -0.4257944 
logit RMSE 756 : 0.06722078 

boosting 756 : -0.7640793 
boosting mean 756 : -0.5060049 
boosting RMSE 756 : 0.1614105 

forest 756 : -0.3570324 
forest mean 756 : -0.3811698 
forest RMSE 756 : 0.05424867 

nnet 756 : -0.738066 
nnet mean 756 : -0.4301467 
nnet RMSE 756 : 0.1557603 


s: 757 
logit 757 : -0.4732098 
logit mean 757 : -0.4258571 
logit RMSE 757 : 0.06722905 

boosting 757 : -0.4423808 
boosting mean 757 : -0.5059208 
boosting RMSE 757 : 0.1613112 

forest 757 : -0.40773 
forest mean 757 : -0.3812049 
forest RMSE 757 : 0.05421355 

nnet 757 : -0.09317115 
nnet mean 757 : -0.4297015 
nnet RMSE 757 : 0.1560564 


s: 758 
logit 758 : -0.4363595 
logit mean 758 : -0.4258709 
logit RMSE 758 : 0.06719767 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 758 : -0.3234301 
boosting mean 758 : -0.5056801 
boosting RMSE 758 : 0.1612288 

forest 758 : -0.3408441 
forest mean 758 : -0.3811516 
forest RMSE 758 : 0.05422037 

nnet 758 : -0.3998761 
nnet mean 758 : -0.4296622 
nnet RMSE 758 : 0.1559534 


s: 759 
logit 759 : -0.4623938 
logit mean 759 : -0.425919 
logit RMSE 759 : 0.06719156 

boosting 759 : -0.5029149 
boosting mean 759 : -0.5056764 
boosting RMSE 759 : 0.1611658 

forest 759 : -0.3183602 
forest mean 759 : -0.3810689 
forest RMSE 759 : 0.05426561 

nnet 759 : -0.4248614 
nnet mean 759 : -0.4296558 
nnet RMSE 759 : 0.1558532 


s: 760 
logit 760 : -0.5199122 
logit mean 760 : -0.4260427 
logit RMSE 760 : 0.06728808 

boosting 760 : -0.6031065 
boosting mean 760 : -0.5058046 
boosting RMSE 760 : 0.1612282 

forest 760 : -0.3518259 
forest mean 760 : -0.3810304 
forest RMSE 760 : 0.05425805 

nnet 760 : -0.4139329 
nnet mean 760 : -0.4296352 
nnet RMSE 760 : 0.1557515 


s: 761 
logit 761 : -0.5145229 
logit mean 761 : -0.426159 
logit RMSE 761 : 0.06737188 

boosting 761 : -0.510935 
boosting mean 761 : -0.5058114 
boosting RMSE 761 : 0.1611724 

forest 761 : -0.4633774 
forest mean 761 : -0.3811386 
forest RMSE 761 : 0.05427103 

nnet 761 : -0.6186078 
nnet mean 761 : -0.4298835 
nnet RMSE 761 : 0.1558507 


s: 762 
logit 762 : -0.4346101 
logit mean 762 : -0.4261701 
logit RMSE 762 : 0.06733933 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 762 : -0.6454285 
boosting mean 762 : -0.5059946 
boosting RMSE 762 : 0.1613118 

forest 762 : -0.3871265 
forest mean 762 : -0.3811465 
forest RMSE 762 : 0.05423742 

nnet 762 : -0.3545267 
nnet mean 762 : -0.4297846 
nnet RMSE 762 : 0.1557571 


s: 763 
logit 763 : -0.4514292 
logit mean 763 : -0.4262032 
logit RMSE 763 : 0.06732094 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 763 : -0.6032612 
boosting mean 763 : -0.5061221 
boosting RMSE 763 : 0.1613739 

forest 763 : -0.4188329 
forest mean 763 : -0.3811959 
forest RMSE 763 : 0.05420615 

nnet 763 : -0.662886 
nnet mean 763 : -0.4300901 
nnet RMSE 763 : 0.1559457 


s: 764 
logit 764 : -0.4152668 
logit mean 764 : -0.4261889 
logit RMSE 764 : 0.06727913 

boosting 764 : -0.3445846 
boosting mean 764 : -0.5059106 
boosting RMSE 764 : 0.1612807 

forest 764 : -0.2872973 
forest mean 764 : -0.381073 
forest RMSE 764 : 0.0543239 

nnet 764 : -0.5645534 
nnet mean 764 : -0.4302661 
nnet RMSE 764 : 0.1559573 


s: 765 
logit 765 : -0.3102075 
logit mean 765 : -0.4260372 
logit RMSE 765 : 0.06731348 

boosting 765 : -0.507059 
boosting mean 765 : -0.5059121 
boosting RMSE 765 : 0.1612217 

forest 765 : -0.3520358 
forest mean 765 : -0.381035 
forest RMSE 765 : 0.05431607 

nnet 765 : -0.3118473 
nnet mean 765 : -0.4301113 
nnet RMSE 765 : 0.1558879 


s: 766 
logit 766 : -0.4259164 
logit mean 766 : -0.4260371 
logit RMSE 766 : 0.06727604 

boosting 766 : -0.6656505 
boosting mean 766 : -0.5061207 
boosting RMSE 766 : 0.1614021 

forest 766 : -0.3554028 
forest mean 766 : -0.3810016 
forest RMSE 766 : 0.05430452 

nnet 766 : -0.5236263 
nnet mean 766 : -0.4302334 
nnet RMSE 766 : 0.1558501 


s: 767 
logit 767 : -0.3859103 
logit mean 767 : -0.4259848 
logit RMSE 767 : 0.0672341 

boosting 767 : -0.5698394 
boosting mean 767 : -0.5062037 
boosting RMSE 767 : 0.1614134 

forest 767 : -0.4058234 
forest mean 767 : -0.3810339 
forest RMSE 767 : 0.05426952 

nnet 767 : -0.4767521 
nnet mean 767 : -0.430294 
nnet RMSE 767 : 0.1557732 


s: 768 
logit 768 : -0.513102 
logit mean 768 : -0.4260982 
logit RMSE 768 : 0.06731415 

boosting 768 : -0.6825361 
boosting mean 768 : -0.5064333 
boosting RMSE 768 : 0.1616302 

forest 768 : -0.4238328 
forest mean 768 : -0.3810897 
forest RMSE 768 : 0.05424099 

nnet 768 : -0.3009869 
nnet mean 768 : -0.4301257 
nnet RMSE 768 : 0.1557127 


s: 769 
logit 769 : -0.4053638 
logit mean 769 : -0.4260712 
logit RMSE 769 : 0.06727064 

boosting 769 : -0.4514177 
boosting mean 769 : -0.5063618 
boosting RMSE 769 : 0.1615357 

forest 769 : -0.2969244 
forest mean 769 : -0.3809802 
forest RMSE 769 : 0.054333 

nnet 769 : -0.3283878 
nnet mean 769 : -0.4299934 
nnet RMSE 769 : 0.1556329 


s: 770 
logit 770 : -0.3950221 
logit mean 770 : -0.4260309 
logit RMSE 770 : 0.06722719 

boosting 770 : -0.548461 
boosting mean 770 : -0.5064165 
boosting RMSE 770 : 0.1615194 

forest 770 : -0.4395337 
forest mean 770 : -0.3810562 
forest RMSE 770 : 0.0543164 

nnet 770 : -0.4286481 
nnet mean 770 : -0.4299916 
nnet RMSE 770 : 0.1555352 


s: 771 
logit 771 : -0.4860716 
logit mean 771 : -0.4261088 
logit RMSE 771 : 0.06725505 

boosting 771 : -0.4500713 
boosting mean 771 : -0.5063434 
boosting RMSE 771 : 0.1614247 

forest 771 : -0.3851248 
forest mean 771 : -0.3810615 
forest RMSE 771 : 0.05428381 

nnet 771 : -0.4806161 
nnet mean 771 : -0.4300573 
nnet RMSE 771 : 0.1554614 


s: 772 
logit 772 : -0.5315574 
logit mean 772 : -0.4262454 
logit RMSE 772 : 0.06737805 

boosting 772 : -0.6424037 
boosting mean 772 : -0.5065196 
boosting RMSE 772 : 0.1615558 

forest 772 : -0.540891 
forest mean 772 : -0.3812686 
forest RMSE 772 : 0.05448511 

nnet 772 : -0.2798859 
nnet mean 772 : -0.4298627 
nnet RMSE 772 : 0.1554208 


s: 773 
logit 773 : -0.5942962 
logit mean 773 : -0.4264628 
logit RMSE 773 : 0.06769612 

boosting 773 : -0.6070522 
boosting mean 773 : -0.5066497 
boosting RMSE 773 : 0.1616230 

forest 773 : -0.3354039 
forest mean 773 : -0.3812092 
forest RMSE 773 : 0.0544994 

nnet 773 : -0.2989468 
nnet mean 773 : -0.4296934 
nnet RMSE 773 : 0.1553628 


s: 774 
logit 774 : -0.4166758 
logit mean 774 : -0.4264501 
logit RMSE 774 : 0.06765503 

boosting 774 : -0.3972375 
boosting mean 774 : -0.5065083 
boosting RMSE 774 : 0.1615185 

forest 774 : -0.3293604 
forest mean 774 : -0.3811422 
forest RMSE 774 : 0.05452334 

nnet 774 : -0.1842320 
nnet mean 774 : -0.4293763 
nnet RMSE 774 : 0.1554560 


s: 775 
logit 775 : -0.3746702 
logit mean 775 : -0.4263833 
logit RMSE 775 : 0.06761749 

boosting 775 : -0.6256161 
boosting mean 775 : -0.506662 
boosting RMSE 775 : 0.1616176 

forest 775 : -0.4301887 
forest mean 775 : -0.3812055 
forest RMSE 775 : 0.05449894 

nnet 775 : -0.4095441 
nnet mean 775 : -0.4293507 
nnet RMSE 775 : 0.1553560 


s: 776 
logit 776 : -0.4661353 
logit mean 776 : -0.4264346 
logit RMSE 776 : 0.0676156 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 776 : -0.4507858 
boosting mean 776 : -0.50659 
boosting RMSE 776 : 0.1615237 

forest 776 : -0.3932669 
forest mean 776 : -0.3812211 
forest RMSE 776 : 0.05446435 

nnet 776 : -0.4139842 
nnet mean 776 : -0.4293309 
nnet RMSE 776 : 0.1552567 


s: 777 
logit 777 : -0.5496073 
logit mean 777 : -0.4265931 
logit RMSE 777 : 0.0677849 

boosting 777 : -0.5098947 
boosting mean 777 : -0.5065943 
boosting RMSE 777 : 0.1614679 

forest 777 : -0.3855824 
forest mean 777 : -0.3812267 
forest RMSE 777 : 0.05443175 

nnet 777 : -0.3939707 
nnet mean 777 : -0.4292854 
nnet RMSE 777 : 0.1551569 


s: 778 
logit 778 : -0.4754706 
logit mean 778 : -0.4266559 
logit RMSE 778 : 0.06779533 

boosting 778 : -0.5689355 
boosting mean 778 : -0.5066744 
boosting RMSE 778 : 0.1614777 

forest 778 : -0.4301644 
forest mean 778 : -0.3812896 
forest RMSE 778 : 0.05440751 

nnet 778 : -0.4337013 
nnet mean 778 : -0.429291 
nnet RMSE 778 : 0.1550619 


s: 779 
logit 779 : -0.4395547 
logit mean 779 : -0.4266725 
logit RMSE 779 : 0.06776662 

boosting 779 : -0.5077476 
boosting mean 779 : -0.5066758 
boosting RMSE 779 : 0.1614202 

forest 779 : -0.4000619 
forest mean 779 : -0.3813137 
forest RMSE 779 : 0.05437257 

nnet 779 : -0.4828561 
nnet mean 779 : -0.4293598 
nnet RMSE 779 : 0.1549907 


s: 780 
logit 780 : -0.4322599 
logit mean 780 : -0.4266796 
logit RMSE 780 : 0.06773302 

boosting 780 : -0.4642212 
boosting mean 780 : -0.5066213 
boosting RMSE 780 : 0.1613331 

forest 780 : -0.3762152 
forest mean 780 : -0.3813071 
forest RMSE 780 : 0.05434438 

nnet 780 : -0.2945861 
nnet mean 780 : -0.429187 
nnet RMSE 780 : 0.1549373 


s: 781 
logit 781 : -0.4045446 
logit mean 781 : -0.4266513 
logit RMSE 781 : 0.06768984 

boosting 781 : -0.2567335 
boosting mean 781 : -0.5063014 
boosting RMSE 781 : 0.1613113 

forest 781 : -0.5397968 
forest mean 781 : -0.3815101 
forest RMSE 781 : 0.05453947 

nnet 781 : -0.6065105 
nnet mean 781 : -0.4294141 
nnet RMSE 781 : 0.1550144 


s: 782 
logit 782 : -0.4683178 
logit mean 782 : -0.4267046 
logit RMSE 782 : 0.06769065 

boosting 782 : -0.6842644 
boosting mean 782 : -0.506529 
boosting RMSE 782 : 0.1615283 

forest 782 : -0.3181146 
forest mean 782 : -0.381429 
forest RMSE 782 : 0.05458319 

nnet 782 : -0.4007704 
nnet mean 782 : -0.4293774 
nnet RMSE 782 : 0.1549152 


s: 783 
logit 783 : -0.3619615 
logit mean 783 : -0.4266219 
logit RMSE 783 : 0.06766106 

boosting 783 : -0.4671004 
boosting mean 783 : -0.5064786 
boosting RMSE 783 : 0.1614429 

forest 783 : -0.4473045 
forest mean 783 : -0.3815131 
forest RMSE 783 : 0.05457451 

nnet 783 : -0.3622749 
nnet mean 783 : -0.4292917 
nnet RMSE 783 : 0.1548221 


s: 784 
logit 784 : -0.4773041 
logit mean 784 : -0.4266865 
logit RMSE 784 : 0.06767424 

boosting 784 : -0.3564728 
boosting mean 784 : -0.5062873 
boosting RMSE 784 : 0.1613474 

forest 784 : -0.3985505 
forest mean 784 : -0.3815349 
forest RMSE 784 : 0.05453972 

nnet 784 : -0.572269 
nnet mean 784 : -0.4294741 
nnet RMSE 784 : 0.1548456 


s: 785 
logit 785 : -0.583991 
logit mean 785 : -0.4268869 
logit RMSE 785 : 0.0679492 

boosting 785 : -0.4409464 
boosting mean 785 : -0.506204 
boosting RMSE 785 : 0.1612512 

forest 785 : -0.4989302 
forest mean 785 : -0.3816844 
forest RMSE 785 : 0.05461922 

nnet 785 : -0.5773689 
nnet mean 785 : -0.4296625 
nnet RMSE 785 : 0.1548764 


s: 786 
logit 786 : -0.4308999 
logit mean 786 : -0.426892 
logit RMSE 786 : 0.0679149 

boosting 786 : -0.9307134 
boosting mean 786 : -0.5067441 
boosting RMSE 786 : 0.1622566 

forest 786 : -0.3784289 
forest mean 786 : -0.3816803 
forest RMSE 786 : 0.05458989 

nnet 786 : -0.6203198 
nnet mean 786 : -0.4299051 
nnet RMSE 786 : 0.1549772 


s: 787 
logit 787 : -0.3560307 
logit mean 787 : -0.426802 
logit RMSE 787 : 0.06788983 

boosting 787 : -0.3742578 
boosting mean 787 : -0.5065758 
boosting RMSE 787 : 0.1621561 

forest 787 : -0.4287328 
forest mean 787 : -0.3817401 
forest RMSE 787 : 0.05456481 

nnet 787 : -0.316625 
nnet mean 787 : -0.4297611 
nnet RMSE 787 : 0.1549072 


s: 788 
logit 788 : -0.4111402 
logit mean 788 : -0.4267821 
logit RMSE 788 : 0.0678479 

boosting 788 : -0.5660741 
boosting mean 788 : -0.5066513 
boosting RMSE 788 : 0.1621611 

forest 788 : -0.3924203 
forest mean 788 : -0.3817536 
forest RMSE 788 : 0.05453084 

nnet 788 : -0.5716674 
nnet mean 788 : -0.4299412 
nnet RMSE 788 : 0.1549297 


s: 789 
logit 789 : -0.3990787 
logit mean 789 : -0.426747 
logit RMSE 789 : 0.0678049 

boosting 789 : -0.4403344 
boosting mean 789 : -0.5065672 
boosting RMSE 789 : 0.1620647 

forest 789 : -0.2998553 
forest mean 789 : -0.3816498 
forest RMSE 789 : 0.05461277 

nnet 789 : -0.3587700 
nnet mean 789 : -0.429851 
nnet RMSE 789 : 0.1548384 


s: 790 
logit 790 : -0.3995297 
logit mean 790 : -0.4267125 
logit RMSE 790 : 0.06776197 

boosting 790 : -0.513802 
boosting mean 790 : -0.5065764 
boosting RMSE 790 : 0.1620127 

forest 790 : -0.3826369 
forest mean 790 : -0.3816511 
forest RMSE 790 : 0.05458169 

nnet 790 : -0.6191326 
nnet mean 790 : -0.4300906 
nnet RMSE 790 : 0.1549367 


s: 791 
logit 791 : -0.452352 
logit mean 791 : -0.4267450 
logit RMSE 791 : 0.0677447 

boosting 791 : -0.1815685 
boosting mean 791 : -0.5061655 
boosting RMSE 791 : 0.1620964 

forest 791 : -0.4175158 
forest mean 791 : -0.3816964 
forest RMSE 791 : 0.05455074 

nnet 791 : -0.02394326 
nnet mean 791 : -0.4295771 
nnet RMSE 791 : 0.1554149 


s: 792 
logit 792 : -0.4236429 
logit mean 792 : -0.426741 
logit RMSE 792 : 0.06770714 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 792 : -0.5724412 
boosting mean 792 : -0.5062492 
boosting RMSE 792 : 0.1621099 

forest 792 : -0.3815281 
forest mean 792 : -0.3816962 
forest RMSE 792 : 0.05452024 

nnet 792 : -0.4883601 
nnet mean 792 : -0.4296514 
nnet RMSE 792 : 0.1553485 


s: 793 
logit 793 : -0.416174 
logit mean 793 : -0.4267277 
logit RMSE 793 : 0.06766687 

boosting 793 : -0.8129049 
boosting mean 793 : -0.5066359 
boosting RMSE 793 : 0.1626698 

forest 793 : -0.3942509 
forest mean 793 : -0.381712 
forest RMSE 793 : 0.05448623 

nnet 793 : -0.7881831 
nnet mean 793 : -0.4301035 
nnet RMSE 793 : 0.1558613 


s: 794 
logit 794 : -0.3995806 
logit mean 794 : -0.4266935 
logit RMSE 794 : 0.06762425 

boosting 794 : -0.4153651 
boosting mean 794 : -0.5065209 
boosting RMSE 794 : 0.1625683 

forest 794 : -0.368407 
forest mean 794 : -0.3816953 
forest RMSE 794 : 0.05446345 

nnet 794 : -0.4799791 
nnet mean 794 : -0.4301663 
nnet RMSE 794 : 0.155789 


s: 795 
logit 795 : -0.3475961 
logit mean 795 : -0.426594 
logit RMSE 795 : 0.06760725 

boosting 795 : -0.5727881 
boosting mean 795 : -0.5066043 
boosting RMSE 795 : 0.1625815 

forest 795 : -0.2542955 
forest mean 795 : -0.381535 
forest RMSE 795 : 0.05467395 

nnet 795 : -0.5962062 
nnet mean 795 : -0.4303751 
nnet RMSE 795 : 0.1558464 


s: 796 
logit 796 : -0.4099485 
logit mean 796 : -0.4265731 
logit RMSE 796 : 0.0675657 

boosting 796 : -0.1682562 
boosting mean 796 : -0.5061792 
boosting RMSE 796 : 0.1626869 

forest 796 : -0.3142504 
forest mean 796 : -0.3814505 
forest RMSE 796 : 0.05472406 

nnet 796 : -0.372351 
nnet mean 796 : -0.4303023 
nnet RMSE 796 : 0.1557516 


s: 797 
logit 797 : -0.4570375 
logit mean 797 : -0.4266113 
logit RMSE 797 : 0.06755351 

boosting 797 : -0.4918588 
boosting mean 797 : -0.5061613 
boosting RMSE 797 : 0.1626173 

forest 797 : -0.5089672 
forest mean 797 : -0.3816105 
forest RMSE 797 : 0.05482576 

nnet 797 : -0.6307977 
nnet mean 797 : -0.4305538 
nnet RMSE 797 : 0.1558684 


s: 798 
logit 798 : -0.4452232 
logit mean 798 : -0.4266347 
logit RMSE 798 : 0.06753015 

boosting 798 : -0.4709073 
boosting mean 798 : -0.5061171 
boosting RMSE 798 : 0.1625348 

forest 798 : -0.3119085 
forest mean 798 : -0.3815231 
forest RMSE 798 : 0.05488006 

nnet 798 : -0.1513387 
nnet mean 798 : -0.4302039 
nnet RMSE 798 : 0.1560192 


s: 799 
logit 799 : -0.4255138 
logit mean 799 : -0.4266333 
logit RMSE 799 : 0.06749391 

boosting 799 : -0.4154983 
boosting mean 799 : -0.5060037 
boosting RMSE 799 : 0.1624340 

forest 799 : -0.3371181 
forest mean 799 : -0.3814676 
forest RMSE 799 : 0.0548908 

nnet 799 : -0.35588 
nnet mean 799 : -0.4301109 
nnet RMSE 799 : 0.1559294 


s: 800 
logit 800 : -0.3558043 
logit mean 800 : -0.4265447 
logit RMSE 800 : 0.06746981 

boosting 800 : -0.4507401 
boosting mean 800 : -0.5059346 
boosting RMSE 800 : 0.1623423 

forest 800 : -0.2920388 
forest mean 800 : -0.3813558 
forest RMSE 800 : 0.05498912 

nnet 800 : -0.302879 
nnet mean 800 : -0.4299519 
nnet RMSE 800 : 0.1558697 


s: 801 
logit 801 : -0.5201305 
logit mean 801 : -0.4266616 
logit RMSE 801 : 0.06756115 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 801 : -0.5007928 
boosting mean 801 : -0.5059282 
boosting RMSE 801 : 0.1622801 

forest 801 : -0.4074593 
forest mean 801 : -0.3813884 
forest RMSE 801 : 0.05495542 

nnet 801 : -0.4540942 
nnet mean 801 : -0.429982 
nnet RMSE 801 : 0.1557841 


s: 802 
logit 802 : -0.4702127 
logit mean 802 : -0.4267159 
logit RMSE 802 : 0.06756452 

boosting 802 : -0.5835845 
boosting mean 802 : -0.506025 
boosting RMSE 802 : 0.1623084 

forest 802 : -0.4256873 
forest mean 802 : -0.3814436 
forest RMSE 802 : 0.05492864 

nnet 802 : -0.3909051 
nnet mean 802 : -0.4299333 
nnet RMSE 802 : 0.1556873 


s: 803 
logit 803 : -0.3978079 
logit mean 803 : -0.4266799 
logit RMSE 803 : 0.06752248 

boosting 803 : -0.6412626 
boosting mean 803 : -0.5061934 
boosting RMSE 803 : 0.1624306 

forest 803 : -0.3842052 
forest mean 803 : -0.3814470 
forest RMSE 803 : 0.05489725 

nnet 803 : -0.7282951 
nnet mean 803 : -0.4303048 
nnet RMSE 803 : 0.1560210 


s: 804 
logit 804 : -0.5359763 
logit mean 804 : -0.4268158 
logit RMSE 804 : 0.06765066 

boosting 804 : -0.655718 
boosting mean 804 : -0.5063794 
boosting RMSE 804 : 0.1625798 

forest 804 : -0.4457954 
forest mean 804 : -0.3815271 
forest RMSE 804 : 0.05488687 

nnet 804 : -0.5455399 
nnet mean 804 : -0.4304482 
nnet RMSE 804 : 0.1560084 


s: 805 
logit 805 : -0.4838879 
logit mean 805 : -0.4268867 
logit RMSE 805 : 0.06767325 

boosting 805 : -0.46194 
boosting mean 805 : -0.5063242 
boosting RMSE 805 : 0.1624935 

forest 805 : -0.3860477 
forest mean 805 : -0.3815327 
forest RMSE 805 : 0.05485497 

nnet 805 : -0.2942789 
nnet mean 805 : -0.430279 
nnet RMSE 805 : 0.1559560 


s: 806 
logit 806 : -0.2943456 
logit mean 806 : -0.4267223 
logit RMSE 806 : 0.06773357 

boosting 806 : -0.5684477 
boosting mean 806 : -0.5064013 
boosting RMSE 806 : 0.162501 

forest 806 : -0.3642606 
forest mean 806 : -0.3815113 
forest RMSE 806 : 0.05483539 

nnet 806 : -0.4123068 
nnet mean 806 : -0.4302567 
nnet RMSE 806 : 0.1558598 


s: 807 
logit 807 : -0.433344 
logit mean 807 : -0.4267305 
logit RMSE 807 : 0.06770176 

boosting 807 : -0.7407002 
boosting mean 807 : -0.5066916 
boosting RMSE 807 : 0.1628425 

forest 807 : -0.3890757 
forest mean 807 : -0.3815206 
forest RMSE 807 : 0.05480275 

nnet 807 : -0.2298292 
nnet mean 807 : -0.4300084 
nnet RMSE 807 : 0.1558784 


s: 808 
logit 808 : -0.3961966 
logit mean 808 : -0.4266927 
logit RMSE 808 : 0.06765999 

boosting 808 : -0.6167333 
boosting mean 808 : -0.5068278 
boosting RMSE 808 : 0.1629203 

forest 808 : -0.382855 
forest mean 808 : -0.3815223 
forest RMSE 808 : 0.05477215 

nnet 808 : -0.3373757 
nnet mean 808 : -0.4298937 
nnet RMSE 808 : 0.1557975 


s: 809 
logit 809 : -0.5096722 
logit mean 809 : -0.4267952 
logit RMSE 809 : 0.06772801 

boosting 809 : -0.329035 
boosting mean 809 : -0.506608 
boosting RMSE 809 : 0.1628386 

forest 809 : -0.3634317 
forest mean 809 : -0.3814999 
forest RMSE 809 : 0.05475338 

nnet 809 : -0.3238886 
nnet mean 809 : -0.4297627 
nnet RMSE 809 : 0.1557242 


s: 810 
logit 810 : -0.4327409 
logit mean 810 : -0.4268026 
logit RMSE 810 : 0.06769596 

boosting 810 : -0.5171912 
boosting mean 810 : -0.5066211 
boosting RMSE 810 : 0.1627902 

forest 810 : -0.4408539 
forest mean 810 : -0.3815732 
forest RMSE 810 : 0.0547384 

nnet 810 : -0.6037734 
nnet mean 810 : -0.4299775 
nnet RMSE 810 : 0.1557926 


s: 811 
logit 811 : -0.4712352 
logit mean 811 : -0.4268574 
logit RMSE 811 : 0.06770044 

boosting 811 : -0.5777477 
boosting mean 811 : -0.5067088 
boosting RMSE 811 : 0.1628095 

forest 811 : -0.3869148 
forest mean 811 : -0.3815798 
forest RMSE 811 : 0.05470657 

nnet 811 : -0.4902858 
nnet mean 811 : -0.4300519 
nnet RMSE 811 : 0.1557288 


s: 812 
logit 812 : -0.42511 
logit mean 812 : -0.4268552 
logit RMSE 812 : 0.06766448 

boosting 812 : -0.4719662 
boosting mean 812 : -0.506666 
boosting RMSE 812 : 0.1627288 

forest 812 : -0.3660544 
forest mean 812 : -0.3815607 
forest RMSE 812 : 0.05468585 

nnet 812 : -0.2214841 
nnet mean 812 : -0.429795 
nnet RMSE 812 : 0.1557589 


s: 813 
logit 813 : -0.3660322 
logit mean 813 : -0.4267804 
logit RMSE 813 : 0.06763335 

boosting 813 : -0.7570708 
boosting mean 813 : -0.506974 
boosting RMSE 813 : 0.1631101 

forest 813 : -0.4160908 
forest mean 813 : -0.3816031 
forest RMSE 813 : 0.05465512 

nnet 813 : -0.1111995 
nnet mean 813 : -0.4294031 
nnet RMSE 813 : 0.1559923 


s: 814 
logit 814 : -0.4119692 
logit mean 814 : -0.4267622 
logit RMSE 814 : 0.06759309 

boosting 814 : -0.4387305 
boosting mean 814 : -0.5068902 
boosting RMSE 814 : 0.1630156 

forest 814 : -0.3333851 
forest mean 814 : -0.3815439 
forest RMSE 814 : 0.05467142 

nnet 814 : -0.5581798 
nnet mean 814 : -0.4295613 
nnet RMSE 814 : 0.1559950 


s: 815 
logit 815 : -0.4377073 
logit mean 815 : -0.4267756 
logit RMSE 815 : 0.06756452 

boosting 815 : -0.5064815 
boosting mean 815 : -0.5068897 
boosting RMSE 815 : 0.1629582 

forest 815 : -0.3458861 
forest mean 815 : -0.3815002 
forest RMSE 815 : 0.05467074 

nnet 815 : -0.2028665 
nnet mean 815 : -0.4292832 
nnet RMSE 815 : 0.1560521 


s: 816 
logit 816 : -0.4840655 
logit mean 816 : -0.4268459 
logit RMSE 816 : 0.06758721 

boosting 816 : -0.768274 
boosting mean 816 : -0.50721 
boosting RMSE 816 : 0.1633678 

forest 816 : -0.4308370 
forest mean 816 : -0.3815606 
forest RMSE 816 : 0.05464789 

nnet 816 : -0.4670055 
nnet mean 816 : -0.4293294 
nnet RMSE 816 : 0.1559741 


s: 817 
logit 817 : -0.3669142 
logit mean 817 : -0.4267725 
logit RMSE 817 : 0.06755575 

boosting 817 : -0.4067811 
boosting mean 817 : -0.5070871 
boosting RMSE 817 : 0.1632680 

forest 817 : -0.3847754 
forest mean 817 : -0.3815646 
forest RMSE 817 : 0.05461703 

nnet 817 : -0.4349729 
nnet mean 817 : -0.4293363 
nnet RMSE 817 : 0.1558834 


s: 818 
logit 818 : -0.4119684 
logit mean 818 : -0.4267544 
logit RMSE 818 : 0.06751574 

boosting 818 : -0.5170765 
boosting mean 818 : -0.5070993 
boosting RMSE 818 : 0.1632195 

forest 818 : -0.3471994 
forest mean 818 : -0.3815225 
forest RMSE 818 : 0.05461485 

nnet 818 : 0.2011261 
nnet mean 818 : -0.4285656 
nnet RMSE 818 : 0.1571995 


s: 819 
logit 819 : -0.4125519 
logit mean 819 : -0.4267371 
logit RMSE 819 : 0.06747594 

boosting 819 : -0.5958908 
boosting mean 819 : -0.5072077 
boosting RMSE 819 : 0.1632634 

forest 819 : -0.4071607 
forest mean 819 : -0.3815538 
forest RMSE 819 : 0.05458207 

nnet 819 : -0.5275539 
nnet mean 819 : -0.4286864 
nnet RMSE 819 : 0.1571667 


s: 820 
logit 820 : -0.4624725 
logit mean 820 : -0.4267806 
logit RMSE 820 : 0.06747006 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 820 : -0.3856887 
boosting mean 820 : -0.5070595 
boosting RMSE 820 : 0.1631645 

forest 820 : -0.2773339 
forest mean 820 : -0.3814267 
forest RMSE 820 : 0.05471672 

nnet 820 : -0.2852783 
nnet mean 820 : -0.4285116 
nnet RMSE 820 : 0.1571219 


s: 821 
logit 821 : -0.3515469 
logit mean 821 : -0.426689 
logit RMSE 821 : 0.06745016 

boosting 821 : -0.3208563 
boosting mean 821 : -0.5068327 
boosting RMSE 821 : 0.1630885 

forest 821 : -0.3406991 
forest mean 821 : -0.3813771 
forest RMSE 821 : 0.05472254 

nnet 821 : -0.4572732 
nnet mean 821 : -0.4285466 
nnet RMSE 821 : 0.1570389 


s: 822 
logit 822 : -0.4726703 
logit mean 822 : -0.4267449 
logit RMSE 822 : 0.06745675 

boosting 822 : -0.4676259 
boosting mean 822 : -0.506785 
boosting RMSE 822 : 0.1630064 

forest 822 : -0.4505102 
forest mean 822 : -0.3814612 
forest RMSE 822 : 0.05471761 

nnet 822 : -0.4329301 
nnet mean 822 : -0.4285519 
nnet RMSE 822 : 0.1569476 


s: 823 
logit 823 : -0.3246576 
logit mean 823 : -0.4266209 
logit RMSE 823 : 0.0674669 

boosting 823 : -0.5794244 
boosting mean 823 : -0.5068733 
boosting RMSE 823 : 0.1630273 

forest 823 : -0.4202151 
forest mean 823 : -0.3815083 
forest RMSE 823 : 0.0546889 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Warning in MatchLoopCfast(N = s1$N, xvars = Kx, All = s1$All, M = s1$M,  :
  Increasing memory because of ties.  I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.
Warning in MatchLoopCfast(N = s1$N, xvars = Kx, All = s1$All, M = s1$M,  :
  Increasing memory because of ties.  I would be faster with the ties=FALSE option.

nnet 823 : -0.1866655 
nnet mean 823 : -0.428258 
nnet RMSE 823 : 0.1570284 


s: 824 
logit 824 : -0.3445884 
logit mean 824 : -0.4265213 
logit RMSE 824 : 0.06745357 

boosting 824 : -0.3380543 
boosting mean 824 : -0.5066684 
boosting RMSE 824 : 0.1629427 

forest 824 : -0.4095754 
forest mean 824 : -0.3815424 
forest RMSE 824 : 0.05465672 

nnet 824 : -0.3616025 
nnet mean 824 : -0.4281771 
nnet RMSE 824 : 0.1569388 


s: 825 
logit 825 : -0.5216686 
logit mean 825 : -0.4266367 
logit RMSE 825 : 0.06754563 

boosting 825 : -0.2632502 
boosting mean 825 : -0.5063733 
boosting RMSE 825 : 0.1629135 

forest 825 : -0.3877405 
forest mean 825 : -0.3815499 
forest RMSE 825 : 0.05462525 

nnet 825 : -0.2591695 
nnet mean 825 : -0.4279723 
nnet RMSE 825 : 0.1569203 


s: 826 
logit 826 : -0.3928524 
logit mean 826 : -0.4265958 
logit RMSE 826 : 0.06750519 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 826 : -0.4556074 
boosting mean 826 : -0.5063119 
boosting RMSE 826 : 0.1628263 

forest 826 : -0.4438246 
forest mean 826 : -0.3816253 
forest RMSE 826 : 0.05461347 

nnet 826 : -0.2960192 
nnet mean 826 : -0.4278125 
nnet RMSE 826 : 0.1568670 


s: 827 
logit 827 : -0.4826466 
logit mean 827 : -0.4266635 
logit RMSE 827 : 0.06752555 

boosting 827 : -0.5070499 
boosting mean 827 : -0.5063128 
boosting RMSE 827 : 0.1627704 

forest 827 : -0.3304841 
forest mean 827 : -0.3815635 
forest RMSE 827 : 0.05463394 

nnet 827 : -0.5284918 
nnet mean 827 : -0.4279343 
nnet RMSE 827 : 0.1568358 


s: 828 
logit 828 : -0.4082259 
logit mean 828 : -0.4266413 
logit RMSE 828 : 0.06748537 

boosting 828 : -0.5055929 
boosting mean 828 : -0.5063119 
boosting RMSE 828 : 0.1627135 

forest 828 : -0.3343993 
forest mean 828 : -0.3815065 
forest RMSE 828 : 0.05464851 

nnet 828 : -0.2930634 
nnet mean 828 : -0.4277714 
nnet RMSE 828 : 0.1567851 


s: 829 
logit 829 : -0.4964941 
logit mean 829 : -0.4267255 
logit RMSE 829 : 0.06752787 

boosting 829 : -0.4967939 
boosting mean 829 : -0.5063004 
boosting RMSE 829 : 0.1626501 

forest 829 : -0.3152175 
forest mean 829 : -0.3814265 
forest RMSE 829 : 0.05469487 

nnet 829 : -0.498764 
nnet mean 829 : -0.427857 
nnet RMSE 829 : 0.1567280 


s: 830 
logit 830 : -0.4062727 
logit mean 830 : -0.4267009 
logit RMSE 830 : 0.06748753 

boosting 830 : -0.6757357 
boosting mean 830 : -0.5065046 
boosting RMSE 830 : 0.1628336 

forest 830 : -0.3938331 
forest mean 830 : -0.3814415 
forest RMSE 830 : 0.05466233 

nnet 830 : -0.6209104 
nnet mean 830 : -0.4280896 
nnet RMSE 830 : 0.1568212 


s: 831 
logit 831 : -0.3523268 
logit mean 831 : -0.4266114 
logit RMSE 831 : 0.06746718 

boosting 831 : -0.6481878 
boosting mean 831 : -0.5066751 
boosting RMSE 831 : 0.1629631 

forest 831 : -0.3999811 
forest mean 831 : -0.3814638 
forest RMSE 831 : 0.05462943 

nnet 831 : -0.1946913 
nnet mean 831 : -0.4278087 
nnet RMSE 831 : 0.1568885 


s: 832 
logit 832 : -0.483243 
logit mean 832 : -0.4266795 
logit RMSE 832 : 0.06748835 

boosting 832 : -0.6729698 
boosting mean 832 : -0.5068749 
boosting RMSE 832 : 0.1631399 

forest 832 : -0.444072 
forest mean 832 : -0.3815390 
forest RMSE 832 : 0.05461796 

nnet 832 : -0.5915026 
nnet mean 832 : -0.4280055 
nnet RMSE 832 : 0.1569347 


s: 833 
logit 833 : -0.4354652 
logit mean 833 : -0.42669 
logit RMSE 833 : 0.06745903 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 833 : -0.7016514 
boosting mean 833 : -0.5071087 
boosting RMSE 833 : 0.1633766 

forest 833 : -0.4496776 
forest mean 833 : -0.3816208 
forest RMSE 833 : 0.0546123 

nnet 833 : -0.4786345 
nnet mean 833 : -0.4280663 
nnet RMSE 833 : 0.1568641 


s: 834 
logit 834 : -0.4987564 
logit mean 834 : -0.4267764 
logit RMSE 834 : 0.06750524 

boosting 834 : -0.4223405 
boosting mean 834 : -0.5070071 
boosting RMSE 834 : 0.1632804 

forest 834 : -0.3637280 
forest mean 834 : -0.3815994 
forest RMSE 834 : 0.054594 

nnet 834 : -0.4026498 
nnet mean 834 : -0.4280358 
nnet RMSE 834 : 0.1567701 


s: 835 
logit 835 : -0.2822560 
logit mean 835 : -0.4266033 
logit RMSE 835 : 0.06758775 

boosting 835 : -0.4638997 
boosting mean 835 : -0.5069555 
boosting RMSE 835 : 0.1631976 

forest 835 : -0.2336119 
forest mean 835 : -0.3814222 
forest RMSE 835 : 0.0548643 

nnet 835 : -0.6422943 
nnet mean 835 : -0.4282924 
nnet RMSE 835 : 0.1569004 


s: 836 
logit 836 : -0.3711451 
logit mean 836 : -0.426537 
logit RMSE 836 : 0.06755468 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 836 : -0.2804700 
boosting mean 836 : -0.5066846 
boosting RMSE 836 : 0.1631524 

forest 836 : -0.3869195 
forest mean 836 : -0.3814287 
forest RMSE 836 : 0.05483334 

nnet 836 : -0.5109545 
nnet mean 836 : -0.4283913 
nnet RMSE 836 : 0.1568535 


s: 837 
logit 837 : -0.487225 
logit mean 837 : -0.4266095 
logit RMSE 837 : 0.0675816 

boosting 837 : -0.5649875 
boosting mean 837 : -0.5067542 
boosting RMSE 837 : 0.1631546 

forest 837 : -0.3265633 
forest mean 837 : -0.3813632 
forest RMSE 837 : 0.05485933 

nnet 837 : -0.5186678 
nnet mean 837 : -0.4284991 
nnet RMSE 837 : 0.1568134 


s: 838 
logit 838 : -0.371092 
logit mean 838 : -0.4265433 
logit RMSE 838 : 0.06754865 

boosting 838 : -0.5035639 
boosting mean 838 : -0.5067504 
boosting RMSE 838 : 0.1630964 

forest 838 : -0.3935799 
forest mean 838 : -0.3813778 
forest RMSE 838 : 0.05482704 

nnet 838 : -0.4432113 
nnet mean 838 : -0.4285167 
nnet RMSE 838 : 0.1567269 


s: 839 
logit 839 : -0.4464581 
logit mean 839 : -0.426567 
logit RMSE 839 : 0.06752743 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 839 : -0.5805648 
boosting mean 839 : -0.5068384 
boosting RMSE 839 : 0.1631184 

forest 839 : -0.3660733 
forest mean 839 : -0.3813595 
forest RMSE 839 : 0.05480687 

nnet 839 : -0.5394504 
nnet mean 839 : -0.4286489 
nnet RMSE 839 : 0.1567075 


s: 840 
logit 840 : -0.5062158 
logit mean 840 : -0.4266618 
logit RMSE 840 : 0.06758665 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 840 : -0.7306833 
boosting mean 840 : -0.5071049 
boosting RMSE 840 : 0.1634200 

forest 840 : -0.366553 
forest mean 840 : -0.3813419 
forest RMSE 840 : 0.05478639 

nnet 840 : -0.3672103 
nnet mean 840 : -0.4285758 
nnet RMSE 840 : 0.1566182 


s: 841 
logit 841 : -0.3745749 
logit mean 841 : -0.4265999 
logit RMSE 841 : 0.06755215 

boosting 841 : -0.8110644 
boosting mean 841 : -0.5074663 
boosting RMSE 841 : 0.1639368 

forest 841 : -0.3714504 
forest mean 841 : -0.3813301 
forest RMSE 841 : 0.05476266 

nnet 841 : -0.4156032 
nnet mean 841 : -0.4285603 
nnet RMSE 841 : 0.1565260 


s: 842 
logit 842 : -0.4751712 
logit mean 842 : -0.4266576 
logit RMSE 842 : 0.06756171 

boosting 842 : -0.5324662 
boosting mean 842 : -0.507496 
boosting RMSE 842 : 0.163903 

forest 842 : -0.3584681 
forest mean 842 : -0.381303 
forest RMSE 842 : 0.05474884 

nnet 842 : -0.4211094 
nnet mean 842 : -0.4285515 
nnet RMSE 842 : 0.1564347 


s: 843 
logit 843 : -0.4233473 
logit mean 843 : -0.4266536 
logit RMSE 843 : 0.06752641 

boosting 843 : -0.706467 
boosting mean 843 : -0.507732 
boosting RMSE 843 : 0.1641455 

forest 843 : -0.3941537 
forest mean 843 : -0.3813182 
forest RMSE 843 : 0.05471673 

nnet 843 : -0.5602272 
nnet mean 843 : -0.4287077 
nnet RMSE 843 : 0.1564393 


s: 844 
logit 844 : -0.3705505 
logit mean 844 : -0.4265872 
logit RMSE 844 : 0.06749401 

boosting 844 : -0.414273 
boosting mean 844 : -0.5076213 
boosting RMSE 844 : 0.1640490 

forest 844 : -0.3072209 
forest mean 844 : -0.3812304 
forest RMSE 844 : 0.05477748 

nnet 844 : -0.2316298 
nnet mean 844 : -0.4284742 
nnet RMSE 844 : 0.1564540 


s: 845 
logit 845 : -0.4167889 
logit mean 845 : -0.4265756 
logit RMSE 845 : 0.06745653 

boosting 845 : -0.4539457 
boosting mean 845 : -0.5075578 
boosting RMSE 845 : 0.1639624 

forest 845 : -0.2759994 
forest mean 845 : -0.3811059 
forest RMSE 845 : 0.054911 

nnet 845 : -0.3018904 
nnet mean 845 : -0.4283244 
nnet RMSE 845 : 0.1563978 


s: 846 
logit 846 : -0.3511814 
logit mean 846 : -0.4264865 
logit RMSE 846 : 0.06743754 

boosting 846 : -0.476542 
boosting mean 846 : -0.5075211 
boosting RMSE 846 : 0.1638866 

forest 846 : -0.5176521 
forest mean 846 : -0.3812673 
forest RMSE 846 : 0.05502741 

nnet 846 : -0.497767 
nnet mean 846 : -0.4284065 
nnet RMSE 846 : 0.1563415 


s: 847 
logit 847 : -0.4199615 
logit mean 847 : -0.4264788 
logit RMSE 847 : 0.06740121 

boosting 847 : -0.3144027 
boosting mean 847 : -0.5072931 
boosting RMSE 847 : 0.1638162 

forest 847 : -0.3383919 
forest mean 847 : -0.3812167 
forest RMSE 847 : 0.05503564 

nnet 847 : -0.2392446 
nnet mean 847 : -0.4281831 
nnet RMSE 847 : 0.1563467 


s: 848 
logit 848 : -0.4274649 
logit mean 848 : -0.4264799 
logit RMSE 848 : 0.06736806 

boosting 848 : -0.475502 
boosting mean 848 : -0.5072556 
boosting RMSE 848 : 0.1637401 

forest 848 : -0.4356445 
forest mean 848 : -0.3812809 
forest RMSE 848 : 0.0550168 

nnet 848 : -0.2034530 
nnet mean 848 : -0.4279181 
nnet RMSE 848 : 0.1564002 


s: 849 
logit 849 : -0.5300166 
logit mean 849 : -0.4266019 
logit RMSE 849 : 0.06747608 

boosting 849 : -0.6449657 
boosting mean 849 : -0.5074178 
boosting RMSE 849 : 0.1638595 

forest 849 : -0.3859771 
forest mean 849 : -0.3812864 
forest RMSE 849 : 0.0549865 

nnet 849 : -0.629549 
nnet mean 849 : -0.4281556 
nnet RMSE 849 : 0.1565065 


s: 850 
logit 850 : -0.4980629 
logit mean 850 : -0.4266859 
logit RMSE 850 : 0.0675202 

boosting 850 : -0.6397075 
boosting mean 850 : -0.5075735 
boosting RMSE 850 : 0.1639693 

forest 850 : -0.4406279 
forest mean 850 : -0.3813562 
forest RMSE 850 : 0.05497181 

nnet 850 : -0.599647 
nnet mean 850 : -0.4283574 
nnet RMSE 850 : 0.1565642 


s: 851 
logit 851 : -0.4415846 
logit mean 851 : -0.4267034 
logit RMSE 851 : 0.06749557 

boosting 851 : -0.4350266 
boosting mean 851 : -0.5074882 
boosting RMSE 851 : 0.1638773 

forest 851 : -0.3189467 
forest mean 851 : -0.3812829 
forest RMSE 851 : 0.05500971 

nnet 851 : -0.8788913 
nnet mean 851 : -0.4288868 
nnet RMSE 851 : 0.157331 


s: 852 
logit 852 : -0.3750922 
logit mean 852 : -0.4266429 
logit RMSE 852 : 0.06746135 

boosting 852 : -0.5924401 
boosting mean 852 : -0.5075879 
boosting RMSE 852 : 0.1639138 

forest 852 : -0.5153114 
forest mean 852 : -0.3814402 
forest RMSE 852 : 0.05511917 

nnet 852 : -0.5713015 
nnet mean 852 : -0.4290539 
nnet RMSE 852 : 0.1573481 


s: 853 
logit 853 : -0.4675121 
logit mean 853 : -0.4266908 
logit RMSE 853 : 0.06746141 

boosting 853 : -0.4991318 
boosting mean 853 : -0.507578 
boosting RMSE 853 : 0.1638528 

forest 853 : -0.4312605 
forest mean 853 : -0.3814986 
forest RMSE 853 : 0.05509725 

nnet 853 : -0.4242898 
nnet mean 853 : -0.4290483 
nnet RMSE 853 : 0.1572581 


s: 854 
logit 854 : -0.3865379 
logit mean 854 : -0.4266438 
logit RMSE 854 : 0.06742347 

boosting 854 : -0.6244218 
boosting mean 854 : -0.5077148 
boosting RMSE 854 : 0.1639368 

forest 854 : -0.3721241 
forest mean 854 : -0.3814876 
forest RMSE 854 : 0.05507324 

nnet 854 : -0.2453158 
nnet mean 854 : -0.4288332 
nnet RMSE 854 : 0.1572551 


s: 855 
logit 855 : -0.4695297 
logit mean 855 : -0.4266939 
logit RMSE 855 : 0.06742598 

boosting 855 : -0.4636580 
boosting mean 855 : -0.5076633 
boosting RMSE 855 : 0.1638554 

forest 855 : -0.4336183 
forest mean 855 : -0.3815486 
forest RMSE 855 : 0.05505304 

nnet 855 : -0.5006261 
nnet mean 855 : -0.4289172 
nnet RMSE 855 : 0.1572008 


s: 856 
logit 856 : -0.5604152 
logit mean 856 : -0.4268501 
logit RMSE 856 : 0.06760927 

boosting 856 : -0.3162165 
boosting mean 856 : -0.5074396 
boosting RMSE 856 : 0.1637847 

forest 856 : -0.4139922 
forest mean 856 : -0.3815865 
forest RMSE 856 : 0.05502295 

nnet 856 : -0.4787471 
nnet mean 856 : -0.4289754 
nnet RMSE 856 : 0.1571320 


s: 857 
logit 857 : -0.4845935 
logit mean 857 : -0.4269175 
logit RMSE 857 : 0.06763157 

boosting 857 : -0.4192303 
boosting mean 857 : -0.5073367 
boosting RMSE 857 : 0.1636904 

forest 857 : -0.4088992 
forest mean 857 : -0.3816184 
forest RMSE 857 : 0.05499168 

nnet 857 : -0.6601587 
nnet mean 857 : -0.4292451 
nnet RMSE 857 : 0.1572915 


s: 858 
logit 858 : -0.4456859 
logit mean 858 : -0.4269394 
logit RMSE 858 : 0.06761014 

boosting 858 : -0.4388596 
boosting mean 858 : -0.5072569 
boosting RMSE 858 : 0.1636004 

forest 858 : -0.3208143 
forest mean 858 : -0.3815475 
forest RMSE 858 : 0.05502607 

nnet 858 : -0.5843952 
nnet mean 858 : -0.429426 
nnet RMSE 858 : 0.1573258 


s: 859 
logit 859 : -0.4498315 
logit mean 859 : -0.4269660 
logit RMSE 859 : 0.06759216 

boosting 859 : -0.5711312 
boosting mean 859 : -0.5073313 
boosting RMSE 859 : 0.1636094 

forest 859 : -0.3893547 
forest mean 859 : -0.3815566 
forest RMSE 859 : 0.05499523 

nnet 859 : -0.5509447 
nnet mean 859 : -0.4295674 
nnet RMSE 859 : 0.1573186 


s: 860 
logit 860 : -0.3854305 
logit mean 860 : -0.4269177 
logit RMSE 860 : 0.06755468 

boosting 860 : -0.7374778 
boosting mean 860 : -0.5075989 
boosting RMSE 860 : 0.1639187 

forest 860 : -0.3282922 
forest mean 860 : -0.3814946 
forest RMSE 860 : 0.05501761 

nnet 860 : -0.5643513 
nnet mean 860 : -0.4297242 
nnet RMSE 860 : 0.1573269 


s: 861 
logit 861 : -0.4295842 
logit mean 861 : -0.4269208 
logit RMSE 861 : 0.06752297 

boosting 861 : -0.4270615 
boosting mean 861 : -0.5075053 
boosting RMSE 861 : 0.1638260 

forest 861 : -0.3752951 
forest mean 861 : -0.3814874 
forest RMSE 861 : 0.0549921 

nnet 861 : -0.407678 
nnet mean 861 : -0.4296986 
nnet RMSE 861 : 0.1572357 


s: 862 
logit 862 : -0.4934422 
logit mean 862 : -0.426998 
logit RMSE 862 : 0.0675588 

boosting 862 : -0.6532396 
boosting mean 862 : -0.5076744 
boosting RMSE 862 : 0.1639580 

forest 862 : -0.3490025 
forest mean 862 : -0.3814498 
forest RMSE 862 : 0.05498763 

nnet 862 : -0.3275802 
nnet mean 862 : -0.4295801 
nnet RMSE 862 : 0.1571639 


s: 863 
logit 863 : -0.4468618 
logit mean 863 : -0.427021 
logit RMSE 863 : 0.06753848 

boosting 863 : -0.4787515 
boosting mean 863 : -0.5076409 
boosting RMSE 863 : 0.1638849 

forest 863 : -0.3416148 
forest mean 863 : -0.3814036 
forest RMSE 863 : 0.05499169 

nnet 863 : -0.5605223 
nnet mean 863 : -0.4297318 
nnet RMSE 863 : 0.1571678 


s: 864 
logit 864 : -0.3791109 
logit mean 864 : -0.4269656 
logit RMSE 864 : 0.06750313 

boosting 864 : -0.6046096 
boosting mean 864 : -0.5077531 
boosting RMSE 864 : 0.1639379 

forest 864 : -0.3581799 
forest mean 864 : -0.3813767 
forest RMSE 864 : 0.05497827 

nnet 864 : -0.4217933 
nnet mean 864 : -0.4297226 
nnet RMSE 864 : 0.1570786 


s: 865 
logit 865 : -0.4198346 
logit mean 865 : -0.4269573 
logit RMSE 865 : 0.06746747 

boosting 865 : -0.3729719 
boosting mean 865 : -0.5075973 
boosting RMSE 865 : 0.1638457 

forest 865 : -0.3941383 
forest mean 865 : -0.3813915 
forest RMSE 865 : 0.05494684 

nnet 865 : -0.03714138 
nnet mean 865 : -0.4292688 
nnet RMSE 865 : 0.1574718 


s: 866 
logit 866 : -0.3683887 
logit mean 866 : -0.4268897 
logit RMSE 866 : 0.06743706 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 866 : -0.6389498 
boosting mean 866 : -0.507749 
boosting RMSE 866 : 0.1639523 

forest 866 : -0.3622478 
forest mean 866 : -0.3813694 
forest RMSE 866 : 0.05493009 

nnet 866 : -0.5372977 
nnet mean 866 : -0.4293935 
nnet RMSE 866 : 0.15745 


s: 867 
logit 867 : -0.3270716 
logit mean 867 : -0.4267746 
logit RMSE 867 : 0.06744365 

boosting 867 : -0.3316985 
boosting mean 867 : -0.5075459 
boosting RMSE 867 : 0.1638741 

forest 867 : -0.2822467 
forest mean 867 : -0.381255 
forest RMSE 867 : 0.05504387 

nnet 867 : -0.2774748 
nnet mean 867 : -0.4292183 
nnet RMSE 867 : 0.1574142 


s: 868 
logit 868 : -0.4079538 
logit mean 868 : -0.4267529 
logit RMSE 868 : 0.06740533 

boosting 868 : -0.3815394 
boosting mean 868 : -0.5074007 
boosting RMSE 868 : 0.1637809 

forest 868 : -0.3742249 
forest mean 868 : -0.3812469 
forest RMSE 868 : 0.05501911 

nnet 868 : -0.3930404 
nnet mean 868 : -0.4291766 
nnet RMSE 868 : 0.1573237 


s: 869 
logit 869 : -0.5438981 
logit mean 869 : -0.4268877 
logit RMSE 869 : 0.06754316 

boosting 869 : -0.5015211 
boosting mean 869 : -0.507394 
boosting RMSE 869 : 0.1637229 

forest 869 : -0.4093911 
forest mean 869 : -0.3812793 
forest RMSE 869 : 0.05498836 

nnet 869 : -0.3019856 
nnet mean 869 : -0.4290303 
nnet RMSE 869 : 0.1572683 


s: 870 
logit 870 : -0.4620392 
logit mean 870 : -0.4269281 
logit RMSE 870 : 0.06753709 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 870 : -0.3424826 
boosting mean 870 : -0.5072044 
boosting RMSE 870 : 0.1636403 

forest 870 : -0.3668265 
forest mean 870 : -0.3812627 
forest RMSE 870 : 0.05496826 

nnet 870 : -0.4746102 
nnet mean 870 : -0.4290826 
nnet RMSE 870 : 0.1571982 


s: 871 
logit 871 : -0.5225888 
logit mean 871 : -0.4270379 
logit RMSE 871 : 0.067626 

boosting 871 : -0.4529237 
boosting mean 871 : -0.5071421 
boosting RMSE 871 : 0.1635562 

forest 871 : -0.3305193 
forest mean 871 : -0.3812045 
forest RMSE 871 : 0.05498712 

nnet 871 : -0.3657672 
nnet mean 871 : -0.4290100 
nnet RMSE 871 : 0.1571122 


s: 872 
logit 872 : -0.3927129 
logit mean 872 : -0.4269986 
logit RMSE 872 : 0.06758766 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 872 : -0.6276991 
boosting mean 872 : -0.5072804 
boosting RMSE 872 : 0.1636442 

forest 872 : -0.4078304 
forest mean 872 : -0.381235 
forest RMSE 872 : 0.05495622 

nnet 872 : -0.3654484 
nnet mean 872 : -0.4289371 
nnet RMSE 872 : 0.1570265 


s: 873 
logit 873 : -0.3816424 
logit mean 873 : -0.4269466 
logit RMSE 873 : 0.0675518 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 873 : -0.2490222 
boosting mean 873 : -0.5069845 
boosting RMSE 873 : 0.1636302 

forest 873 : -0.3880294 
forest mean 873 : -0.3812428 
forest RMSE 873 : 0.05492623 

nnet 873 : -0.3751565 
nnet mean 873 : -0.4288755 
nnet RMSE 873 : 0.1569388 


s: 874 
logit 874 : -0.5442666 
logit mean 874 : -0.4270808 
logit RMSE 874 : 0.06768927 

boosting 874 : -0.6436659 
boosting mean 874 : -0.5071409 
boosting RMSE 874 : 0.1637442 

forest 874 : -0.3708427 
forest mean 874 : -0.3812309 
forest RMSE 874 : 0.05490366 

nnet 874 : -0.3381506 
nnet mean 874 : -0.4287717 
nnet RMSE 874 : 0.1568629 


s: 875 
logit 875 : -0.3915119 
logit mean 875 : -0.4270402 
logit RMSE 875 : 0.06765119 

boosting 875 : -0.4003099 
boosting mean 875 : -0.5070188 
boosting RMSE 875 : 0.1636506 

forest 875 : -0.4429236 
forest mean 875 : -0.3813014 
forest RMSE 875 : 0.05489146 

nnet 875 : 0.0925431 
nnet mean 875 : -0.4281759 
nnet RMSE 875 : 0.1576550 


s: 876 
logit 876 : -0.3157946 
logit mean 876 : -0.4269132 
logit RMSE 876 : 0.0676724 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 876 : -0.3710194 
boosting mean 876 : -0.5068636 
boosting RMSE 876 : 0.1635601 

forest 876 : -0.3440221 
forest mean 876 : -0.3812588 
forest RMSE 876 : 0.05489271 

nnet 876 : -0.4756039 
nnet mean 876 : -0.42823 
nnet RMSE 876 : 0.1575857 


s: 877 
logit 877 : -0.4394537 
logit mean 877 : -0.4269275 
logit RMSE 877 : 0.06764692 

boosting 877 : -0.5125981 
boosting mean 877 : -0.5068701 
boosting RMSE 877 : 0.163511 

forest 877 : -0.4195596 
forest mean 877 : -0.3813025 
forest RMSE 877 : 0.05486538 

nnet 877 : -0.1141984 
nnet mean 877 : -0.4278719 
nnet RMSE 877 : 0.1577912 


s: 878 
logit 878 : -0.4389951 
logit mean 878 : -0.4269412 
logit RMSE 878 : 0.0676212 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 878 : -0.4478054 
boosting mean 878 : -0.5068028 
boosting RMSE 878 : 0.1634258 

forest 878 : -0.3971469 
forest mean 878 : -0.3813205 
forest RMSE 878 : 0.05483421 

nnet 878 : -0.5943028 
nnet mean 878 : -0.4280615 
nnet RMSE 878 : 0.1578376 


s: 879 
logit 879 : -0.4930218 
logit mean 879 : -0.4270164 
logit RMSE 879 : 0.06765551 

boosting 879 : -0.3455779 
boosting mean 879 : -0.5066194 
boosting RMSE 879 : 0.1633431 

forest 879 : -0.4239057 
forest mean 879 : -0.381369 
forest RMSE 879 : 0.05480894 

nnet 879 : -0.4084571 
nnet mean 879 : -0.4280392 
nnet RMSE 879 : 0.1577481 


s: 880 
logit 880 : -0.4786957 
logit mean 880 : -0.4270751 
logit RMSE 880 : 0.06766908 

boosting 880 : -0.5517071 
boosting mean 880 : -0.5066707 
boosting RMSE 880 : 0.1633304 

forest 880 : -0.3319545 
forest mean 880 : -0.3813128 
forest RMSE 880 : 0.0548258 

nnet 880 : -0.371585 
nnet mean 880 : -0.427975 
nnet RMSE 880 : 0.1576613 


s: 881 
logit 881 : -0.4815628 
logit mean 881 : -0.427137 
logit RMSE 881 : 0.06768647 

boosting 881 : -0.3666656 
boosting mean 881 : -0.5065117 
boosting RMSE 881 : 0.1632415 

forest 881 : -0.3768220 
forest mean 881 : -0.3813077 
forest RMSE 881 : 0.05480024 

nnet 881 : -0.4111159 
nnet mean 881 : -0.4279559 
nnet RMSE 881 : 0.1575723 


s: 882 
logit 882 : -0.4111544 
logit mean 882 : -0.4271189 
logit RMSE 882 : 0.06764913 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 882 : -0.4981482 
boosting mean 882 : -0.5065023 
boosting RMSE 882 : 0.1631824 

forest 882 : -0.365566 
forest mean 882 : -0.3812899 
forest RMSE 882 : 0.05478144 

nnet 882 : -0.6403095 
nnet mean 882 : -0.4281967 
nnet RMSE 882 : 0.1576907 


s: 883 
logit 883 : -0.3806538 
logit mean 883 : -0.4270663 
logit RMSE 883 : 0.06761395 

boosting 883 : -0.3282407 
boosting mean 883 : -0.5063004 
boosting RMSE 883 : 0.1631079 

forest 883 : -0.4614389 
forest mean 883 : -0.3813807 
forest RMSE 883 : 0.05478943 

nnet 883 : -0.3987372 
nnet mean 883 : -0.4281633 
nnet RMSE 883 : 0.1576014 


s: 884 
logit 884 : -0.4028946 
logit mean 884 : -0.4270389 
logit RMSE 884 : 0.06757576 

boosting 884 : -0.4964429 
boosting mean 884 : -0.5062892 
boosting RMSE 884 : 0.1630479 

forest 884 : -0.3931226 
forest mean 884 : -0.3813939 
forest RMSE 884 : 0.05475892 

nnet 884 : -0.296642 
nnet mean 884 : -0.4280145 
nnet RMSE 884 : 0.1575506 


s: 885 
logit 885 : -0.3804641 
logit mean 885 : -0.4269863 
logit RMSE 885 : 0.06754076 

boosting 885 : -0.4749363 
boosting mean 885 : -0.5062538 
boosting RMSE 885 : 0.1629752 

forest 885 : -0.2821716 
forest mean 885 : -0.3812818 
forest RMSE 885 : 0.05487111 

nnet 885 : -0.5457884 
nnet mean 885 : -0.4281476 
nnet RMSE 885 : 0.1575378 


s: 886 
logit 886 : -0.5694704 
logit mean 886 : -0.4271471 
logit RMSE 886 : 0.06774232 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 886 : -0.5262827 
boosting mean 886 : -0.5062764 
boosting RMSE 886 : 0.1629384 

forest 886 : -0.3985683 
forest mean 886 : -0.3813013 
forest RMSE 886 : 0.05484016 

nnet 886 : -0.5779056 
nnet mean 886 : -0.4283166 
nnet RMSE 886 : 0.1575622 


s: 887 
logit 887 : -0.3625771 
logit mean 887 : -0.4270743 
logit RMSE 887 : 0.06771578 

boosting 887 : -0.1735415 
boosting mean 887 : -0.5059013 
boosting RMSE 887 : 0.163024 

forest 887 : -0.3779213 
forest mean 887 : -0.3812975 
forest RMSE 887 : 0.05481425 

nnet 887 : -0.2335384 
nnet mean 887 : -0.428097 
nnet RMSE 887 : 0.1575725 


s: 888 
logit 888 : -0.3954401 
logit mean 888 : -0.4270387 
logit RMSE 888 : 0.06767782 

boosting 888 : -0.428139 
boosting mean 888 : -0.5058137 
boosting RMSE 888 : 0.1629349 

forest 888 : -0.3427912 
forest mean 888 : -0.3812542 
forest RMSE 888 : 0.05481701 

nnet 888 : -0.5041274 
nnet mean 888 : -0.4281826 
nnet RMSE 888 : 0.1575226 


s: 889 
logit 889 : -0.3967161 
logit mean 889 : -0.4270046 
logit RMSE 889 : 0.06763983 

boosting 889 : -0.4648474 
boosting mean 889 : -0.5057676 
boosting RMSE 889 : 0.1628578 

forest 889 : -0.3842712 
forest mean 889 : -0.3812576 
forest RMSE 889 : 0.05478871 

nnet 889 : -0.2955915 
nnet mean 889 : -0.4280335 
nnet RMSE 889 : 0.1574729 


s: 890 
logit 890 : -0.4314157 
logit mean 890 : -0.4270095 
logit RMSE 890 : 0.06761002 

boosting 890 : -0.5724472 
boosting mean 890 : -0.5058426 
boosting RMSE 890 : 0.1628689 

forest 890 : -0.4023748 
forest mean 890 : -0.3812813 
forest RMSE 890 : 0.05475798 

nnet 890 : -0.1898238 
nnet mean 890 : -0.4277658 
nnet RMSE 890 : 0.157542 


s: 891 
logit 891 : -0.3337255 
logit mean 891 : -0.4269048 
logit RMSE 891 : 0.06760854 

boosting 891 : -0.4968946 
boosting mean 891 : -0.5058325 
boosting RMSE 891 : 0.1628098 

forest 891 : -0.3644036 
forest mean 891 : -0.3812623 
forest RMSE 891 : 0.05474023 

nnet 891 : -0.4517203 
nnet mean 891 : -0.4277927 
nnet RMSE 891 : 0.1574631 


s: 892 
logit 892 : -0.5390697 
logit mean 892 : -0.4270306 
logit RMSE 892 : 0.06773088 

boosting 892 : -0.5120182 
boosting mean 892 : -0.5058394 
boosting RMSE 892 : 0.1627617 

forest 892 : -0.4163155 
forest mean 892 : -0.3813016 
forest RMSE 892 : 0.05471226 

nnet 892 : -0.3238448 
nnet mean 892 : -0.4276762 
nnet RMSE 892 : 0.1573955 


s: 893 
logit 893 : -0.4082182 
logit mean 893 : -0.4270095 
logit RMSE 893 : 0.0676935 

boosting 893 : -0.5158889 
boosting mean 893 : -0.5058507 
boosting RMSE 893 : 0.1627168 

forest 893 : -0.4395523 
forest mean 893 : -0.3813669 
forest RMSE 893 : 0.05469764 

nnet 893 : -0.485567 
nnet mean 893 : -0.427741 
nnet RMSE 893 : 0.1573334 


s: 894 
logit 894 : -0.2553346 
logit mean 894 : -0.4268175 
logit RMSE 894 : 0.06782842 

boosting 894 : -0.5000213 
boosting mean 894 : -0.5058442 
boosting RMSE 894 : 0.1626602 

forest 894 : -0.3245820 
forest mean 894 : -0.3813033 
forest RMSE 894 : 0.0547252 

nnet 894 : -0.5397282 
nnet mean 894 : -0.4278663 
nnet RMSE 894 : 0.1573148 


s: 895 
logit 895 : -0.4367812 
logit mean 895 : -0.4268286 
logit RMSE 895 : 0.06780166 

boosting 895 : -0.3790455 
boosting mean 895 : -0.5057025 
boosting RMSE 895 : 0.1625708 

forest 895 : -0.476237 
forest mean 895 : -0.3814094 
forest RMSE 895 : 0.05475395 

nnet 895 : -0.2200471 
nnet mean 895 : -0.4276341 
nnet RMSE 895 : 0.1573419 


s: 896 
logit 896 : -0.4571907 
logit mean 896 : -0.4268625 
logit RMSE 896 : 0.06779074 

boosting 896 : -0.5044852 
boosting mean 896 : -0.5057011 
boosting RMSE 896 : 0.1625175 

forest 896 : -0.4180531 
forest mean 896 : -0.3814503 
forest RMSE 896 : 0.05472671 

nnet 896 : -0.1454730 
nnet mean 896 : -0.4273192 
nnet RMSE 896 : 0.1574838 


s: 897 
logit 897 : -0.3750606 
logit mean 897 : -0.4268047 
logit RMSE 897 : 0.06775806 

boosting 897 : -0.7014413 
boosting mean 897 : -0.5059194 
boosting RMSE 897 : 0.1627384 

forest 897 : -0.4096324 
forest mean 897 : -0.3814817 
forest RMSE 897 : 0.05469714 

nnet 897 : -0.5280684 
nnet mean 897 : -0.4274315 
nnet RMSE 897 : 0.1574540 


s: 898 
logit 898 : -0.3764995 
logit mean 898 : -0.4267487 
logit RMSE 898 : 0.06772487 

boosting 898 : -0.3906729 
boosting mean 898 : -0.505791 
boosting RMSE 898 : 0.1626481 

forest 898 : -0.3842412 
forest mean 898 : -0.3814848 
forest RMSE 898 : 0.05466921 

nnet 898 : -0.3831803 
nnet mean 898 : -0.4273822 
nnet RMSE 898 : 0.1573674 


s: 899 
logit 899 : -0.394487 
logit mean 899 : -0.4267128 
logit RMSE 899 : 0.06768744 

boosting 899 : -0.4939087 
boosting mean 899 : -0.5057778 
boosting RMSE 899 : 0.1625878 

forest 899 : -0.3206962 
forest mean 899 : -0.3814172 
forest RMSE 899 : 0.05470277 

nnet 899 : -0.432233 
nnet mean 899 : -0.4273876 
nnet RMSE 899 : 0.1572835 


s: 900 
logit 900 : -0.4512254 
logit mean 900 : -0.4267401 
logit RMSE 900 : 0.06767137 

boosting 900 : -0.7242221 
boosting mean 900 : -0.5060205 
boosting RMSE 900 : 0.1628564 

forest 900 : -0.416792 
forest mean 900 : -0.3814565 
forest RMSE 900 : 0.05467524 

nnet 900 : -0.3097463 
nnet mean 900 : -0.4272569 
nnet RMSE 900 : 0.1572249 


s: 901 
logit 901 : -0.3904640 
logit mean 901 : -0.4266998 
logit RMSE 901 : 0.06763455 

boosting 901 : -0.3702018 
boosting mean 901 : -0.5058698 
boosting RMSE 901 : 0.1627691 

forest 901 : -0.4065821 
forest mean 901 : -0.3814844 
forest RMSE 901 : 0.05464533 

nnet 901 : -0.4380594 
nnet mean 901 : -0.4272689 
nnet RMSE 901 : 0.1571427 


s: 902 
logit 902 : -0.4013056 
logit mean 902 : -0.4266717 
logit RMSE 902 : 0.06759706 

boosting 902 : -0.594921 
boosting mean 902 : -0.5059685 
boosting RMSE 902 : 0.1628082 

forest 902 : -0.3560142 
forest mean 902 : -0.3814561 
forest RMSE 902 : 0.05463466 

nnet 902 : -0.6112952 
nnet mean 902 : -0.4274729 
nnet RMSE 902 : 0.1572131 


s: 903 
logit 903 : -0.3277653 
logit mean 903 : -0.4265621 
logit RMSE 903 : 0.06760238 

boosting 903 : -0.5786362 
boosting mean 903 : -0.506049 
boosting RMSE 903 : 0.1628266 

forest 903 : -0.3177233 
forest mean 903 : -0.3813856 
forest RMSE 903 : 0.05467301 

nnet 903 : -0.3295429 
nnet mean 903 : -0.4273645 
nnet RMSE 903 : 0.1571435 


s: 904 
logit 904 : -0.4064107 
logit mean 904 : -0.4265398 
logit RMSE 904 : 0.06756531 

boosting 904 : -0.403768 
boosting mean 904 : -0.5059358 
boosting RMSE 904 : 0.1627366 

forest 904 : -0.3213818 
forest mean 904 : -0.3813192 
forest RMSE 904 : 0.05470529 

nnet 904 : -0.3610818 
nnet mean 904 : -0.4272911 
nnet RMSE 904 : 0.1570619 


s: 905 
logit 905 : -0.4050577 
logit mean 905 : -0.4265161 
logit RMSE 905 : 0.06752818 

boosting 905 : -0.6620505 
boosting mean 905 : -0.5061083 
boosting RMSE 905 : 0.1628797 

forest 905 : -0.3974590 
forest mean 905 : -0.381337 
forest RMSE 905 : 0.05467512 

nnet 905 : -0.5578267 
nnet mean 905 : -0.4274354 
nnet RMSE 905 : 0.1570627 


s: 906 
logit 906 : -0.3672383 
logit mean 906 : -0.4264507 
logit RMSE 906 : 0.06749968 

boosting 906 : -0.3982515 
boosting mean 906 : -0.5059893 
boosting RMSE 906 : 0.1627898 

forest 906 : -0.507385 
forest mean 906 : -0.3814761 
forest RMSE 906 : 0.05476127 

nnet 906 : -0.2293517 
nnet mean 906 : -0.4272167 
nnet RMSE 906 : 0.1570784 


s: 907 
logit 907 : -0.4147216 
logit mean 907 : -0.4264377 
logit RMSE 907 : 0.06746423 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 907 : -0.3502599 
boosting mean 907 : -0.5058176 
boosting RMSE 907 : 0.1627084 

forest 907 : -0.4445278 
forest mean 907 : -0.3815457 
forest RMSE 907 : 0.05475104 

nnet 907 : -0.5202558 
nnet mean 907 : -0.4273193 
nnet RMSE 907 : 0.1570425 


s: 908 
logit 908 : -0.5136947 
logit mean 908 : -0.4265338 
logit RMSE 908 : 0.06753256 

boosting 908 : -0.6141206 
boosting mean 908 : -0.5059369 
boosting RMSE 908 : 0.162774 

forest 908 : -0.3834877 
forest mean 908 : -0.3815478 
forest RMSE 908 : 0.05472363 

nnet 908 : -0.3879614 
nnet mean 908 : -0.427276 
nnet RMSE 908 : 0.1569565 


s: 909 
logit 909 : -0.4980508 
logit mean 909 : -0.4266125 
logit RMSE 909 : 0.0675737 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 909 : -0.5556828 
boosting mean 909 : -0.5059916 
boosting RMSE 909 : 0.1627664 

forest 909 : -0.4848211 
forest mean 909 : -0.3816614 
forest RMSE 909 : 0.05476583 

nnet 909 : -0.5167579 
nnet mean 909 : -0.4273744 
nnet RMSE 909 : 0.1569180 


s: 910 
logit 910 : -0.5072191 
logit mean 910 : -0.4267011 
logit RMSE 910 : 0.06763003 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 910 : -0.5316951 
boosting mean 910 : -0.5060198 
boosting RMSE 910 : 0.1627355 

forest 910 : -0.3651785 
forest mean 910 : -0.3816433 
forest RMSE 910 : 0.0547479 

nnet 910 : -0.461934 
nnet mean 910 : -0.4274124 
nnet RMSE 910 : 0.1568452 


s: 911 
logit 911 : -0.4567593 
logit mean 911 : -0.4267341 
logit RMSE 911 : 0.06761905 

boosting 911 : -0.5943006 
boosting mean 911 : -0.5061168 
boosting RMSE 911 : 0.1627735 

forest 911 : -0.3829557 
forest mean 911 : -0.3816447 
forest RMSE 911 : 0.05472076 

nnet 911 : -0.3431617 
nnet mean 911 : -0.4273199 
nnet RMSE 911 : 0.1567704 


s: 912 
logit 912 : -0.3689169 
logit mean 912 : -0.4266707 
logit RMSE 912 : 0.0675898 

boosting 912 : -0.4366665 
boosting mean 912 : -0.5060406 
boosting RMSE 912 : 0.1626887 

forest 912 : -0.3134253 
forest mean 912 : -0.3815699 
forest RMSE 912 : 0.05476583 

nnet 912 : -0.460995 
nnet mean 912 : -0.4273568 
nnet RMSE 912 : 0.1566974 


s: 913 
logit 913 : -0.4298745 
logit mean 913 : -0.4266742 
logit RMSE 913 : 0.06756002 

boosting 913 : -0.3347117 
boosting mean 913 : -0.5058529 
boosting RMSE 913 : 0.1626140 

forest 913 : -0.3510527 
forest mean 913 : -0.3815365 
forest RMSE 913 : 0.0547598 

nnet 913 : -0.1126978 
nnet mean 913 : -0.4270122 
nnet RMSE 913 : 0.1568999 


s: 914 
logit 914 : -0.3969515 
logit mean 914 : -0.4266417 
logit RMSE 914 : 0.06752312 

boosting 914 : -0.4505848 
boosting mean 914 : -0.5057925 
boosting RMSE 914 : 0.1625336 

forest 914 : -0.3780811 
forest mean 914 : -0.3815327 
forest RMSE 914 : 0.05473463 

nnet 914 : -0.2779678 
nnet mean 914 : -0.4268491 
nnet RMSE 914 : 0.1568660 


s: 915 
logit 915 : -0.4435992 
logit mean 915 : -0.4266602 
logit RMSE 915 : 0.0675016 

boosting 915 : -0.3998757 
boosting mean 915 : -0.5056767 
boosting RMSE 915 : 0.1624448 

forest 915 : -0.3803953 
forest mean 915 : -0.3815315 
forest RMSE 915 : 0.05470856 

nnet 915 : -0.4039195 
nnet mean 915 : -0.4268241 
nnet RMSE 915 : 0.1567803 


s: 916 
logit 916 : -0.3476607 
logit mean 916 : -0.426574 
logit RMSE 916 : 0.06748691 

boosting 916 : -0.5952752 
boosting mean 916 : -0.5057745 
boosting RMSE 916 : 0.1624842 

forest 916 : -0.3130775 
forest mean 916 : -0.3814568 
forest RMSE 916 : 0.05475406 

nnet 916 : -0.2563584 
nnet mean 916 : -0.426638 
nnet RMSE 916 : 0.1567666 


s: 917 
logit 917 : -0.485219 
logit mean 917 : -0.4266379 
logit RMSE 917 : 0.06750878 

boosting 917 : -0.589601 
boosting mean 917 : -0.5058659 
boosting RMSE 917 : 0.1625163 

forest 917 : -0.3512592 
forest mean 917 : -0.3814238 
forest RMSE 917 : 0.05474786 

nnet 917 : -0.5245995 
nnet mean 917 : -0.4267448 
nnet RMSE 917 : 0.1567351 


s: 918 
logit 918 : -0.4440596 
logit mean 918 : -0.4266569 
logit RMSE 918 : 0.06748767 

boosting 918 : -0.5133323 
boosting mean 918 : -0.5058741 
boosting RMSE 918 : 0.1624708 

forest 918 : -0.3516546 
forest mean 918 : -0.3813914 
forest RMSE 918 : 0.0547413 

nnet 918 : -0.4336196 
nnet mean 918 : -0.4267523 
nnet RMSE 918 : 0.1566537 


s: 919 
logit 919 : -0.3885979 
logit mean 919 : -0.4266155 
logit RMSE 919 : 0.067452 

boosting 919 : -0.545094 
boosting mean 919 : -0.5059168 
boosting RMSE 919 : 0.1624529 

forest 919 : -0.3498052 
forest mean 919 : -0.381357 
forest RMSE 919 : 0.05473655 

nnet 919 : -0.3210307 
nnet mean 919 : -0.4266372 
nnet RMSE 919 : 0.1565901 


s: 920 
logit 920 : -0.4786071 
logit mean 920 : -0.426672 
logit RMSE 920 : 0.06746512 

boosting 920 : -0.5166193 
boosting mean 920 : -0.5059284 
boosting RMSE 920 : 0.1624101 

forest 920 : -0.4692163 
forest mean 920 : -0.3814525 
forest RMSE 920 : 0.05475437 

nnet 920 : -0.3728653 
nnet mean 920 : -0.4265788 
nnet RMSE 920 : 0.1565075 


s: 921 
logit 921 : -0.4379845 
logit mean 921 : -0.4266843 
logit RMSE 921 : 0.0674401 

boosting 921 : -0.3815058 
boosting mean 921 : -0.5057933 
boosting RMSE 921 : 0.1623230 

forest 921 : -0.3410783 
forest mean 921 : -0.3814087 
forest RMSE 921 : 0.05475907 

nnet 921 : -0.2282475 
nnet mean 921 : -0.4263635 
nnet RMSE 921 : 0.1565249 


s: 922 
logit 922 : -0.5022637 
logit mean 922 : -0.4267663 
logit RMSE 922 : 0.0674876 

boosting 922 : -0.4555559 
boosting mean 922 : -0.5057388 
boosting RMSE 922 : 0.1622453 

forest 922 : -0.5345969 
forest mean 922 : -0.3815748 
forest RMSE 922 : 0.05490858 

nnet 922 : -0.3744013 
nnet mean 922 : -0.4263071 
nnet RMSE 922 : 0.1564422 


s: 923 
logit 923 : -0.40992 
logit mean 923 : -0.426748 
logit RMSE 923 : 0.06745183 

boosting 923 : -0.4678086 
boosting mean 923 : -0.5056977 
boosting RMSE 923 : 0.1621727 

forest 923 : -0.2982191 
forest mean 923 : -0.3814845 
forest RMSE 923 : 0.05498099 

nnet 923 : -0.5495361 
nnet mean 923 : -0.4264406 
nnet RMSE 923 : 0.1564349 


s: 924 
logit 924 : -0.5357857 
logit mean 924 : -0.426866 
logit RMSE 924 : 0.06756315 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 924 : -0.4710355 
boosting mean 924 : -0.5056602 
boosting RMSE 924 : 0.1621018 

forest 924 : -0.3784619 
forest mean 924 : -0.3814813 
forest RMSE 924 : 0.0549558 

nnet 924 : -0.4866824 
nnet mean 924 : -0.4265058 
nnet RMSE 924 : 0.1563762 


s: 925 
logit 925 : -0.4252122 
logit mean 925 : -0.4268642 
logit RMSE 925 : 0.0675317 

boosting 925 : -0.5879852 
boosting mean 925 : -0.5057492 
boosting RMSE 925 : 0.1621320 

forest 925 : -0.473451 
forest mean 925 : -0.3815807 
forest RMSE 925 : 0.05497915 

nnet 925 : -0.5441118 
nnet mean 925 : -0.4266329 
nnet RMSE 925 : 0.1563635 


s: 926 
logit 926 : -0.4733765 
logit mean 926 : -0.4269145 
logit RMSE 926 : 0.06753829 

boosting 926 : -0.5444711 
boosting mean 926 : -0.505791 
boosting RMSE 926 : 0.162114 

forest 926 : -0.425223 
forest mean 926 : -0.3816278 
forest RMSE 926 : 0.05495571 

nnet 926 : -0.2646046 
nnet mean 926 : -0.426458 
nnet RMSE 926 : 0.1563424 


s: 927 
logit 927 : -0.2944864 
logit mean 927 : -0.4267716 
logit RMSE 927 : 0.06759075 

boosting 927 : -0.2074315 
boosting mean 927 : -0.5054692 
boosting RMSE 927 : 0.1621499 

forest 927 : -0.4227836 
forest mean 927 : -0.3816722 
forest RMSE 927 : 0.05493116 

nnet 927 : -0.2652866 
nnet mean 927 : -0.4262841 
nnet RMSE 927 : 0.1563207 


s: 928 
logit 928 : -0.4122356 
logit mean 928 : -0.4267559 
logit RMSE 928 : 0.06755552 

boosting 928 : -0.5874624 
boosting mean 928 : -0.5055575 
boosting RMSE 928 : 0.1621793 

forest 928 : -0.3696145 
forest mean 928 : -0.3816592 
forest RMSE 928 : 0.05491061 

nnet 928 : -0.365178 
nnet mean 928 : -0.4262183 
nnet RMSE 928 : 0.1562406 


s: 929 
logit 929 : -0.3213504 
logit mean 929 : -0.4266425 
logit RMSE 929 : 0.06756844 

boosting 929 : -0.4190537 
boosting mean 929 : -0.5054644 
boosting RMSE 929 : 0.1620932 

forest 929 : -0.3803826 
forest mean 929 : -0.3816578 
forest RMSE 929 : 0.05488482 

nnet 929 : -0.1449128 
nnet mean 929 : -0.4259155 
nnet RMSE 929 : 0.1563806 


s: 930 
logit 930 : -0.468519 
logit mean 930 : -0.4266875 
logit RMSE 930 : 0.06756947 

boosting 930 : -0.5800458 
boosting mean 930 : -0.5055446 
boosting RMSE 930 : 0.1621136 

forest 930 : -0.3564951 
forest mean 930 : -0.3816308 
forest RMSE 930 : 0.05487386 

nnet 930 : -0.297017 
nnet mean 930 : -0.4257769 
nnet RMSE 930 : 0.1563330 


s: 931 
logit 931 : -0.4227146 
logit mean 931 : -0.4266832 
logit RMSE 931 : 0.06753728 

boosting 931 : -0.5226615 
boosting mean 931 : -0.505563 
boosting RMSE 931 : 0.1620764 

forest 931 : -0.4109217 
forest mean 931 : -0.3816623 
forest RMSE 931 : 0.05484555 

nnet 931 : -0.5067014 
nnet mean 931 : -0.4258638 
nnet RMSE 931 : 0.1562881 


s: 932 
logit 932 : -0.3260089 
logit mean 932 : -0.4265752 
logit RMSE 932 : 0.06754453 

boosting 932 : -0.4450472 
boosting mean 932 : -0.5054981 
boosting RMSE 932 : 0.1619961 

forest 932 : -0.326903 
forest mean 932 : -0.3816035 
forest RMSE 932 : 0.05486838 

nnet 932 : -0.3524611 
nnet mean 932 : -0.425785 
nnet RMSE 932 : 0.156212 


s: 933 
logit 933 : -0.3947329 
logit mean 933 : -0.4265411 
logit RMSE 933 : 0.06750854 

boosting 933 : -0.6710276 
boosting mean 933 : -0.5056755 
boosting RMSE 933 : 0.1621522 

forest 933 : -0.29109 
forest mean 933 : -0.3815065 
forest RMSE 933 : 0.05495476 

nnet 933 : -0.3672423 
nnet mean 933 : -0.4257223 
nnet RMSE 933 : 0.1561319 


s: 934 
logit 934 : -0.4405828 
logit mean 934 : -0.4265561 
logit RMSE 934 : 0.06748546 

boosting 934 : -0.4646879 
boosting mean 934 : -0.5056316 
boosting RMSE 934 : 0.1620792 

forest 934 : -0.407525 
forest mean 934 : -0.3815343 
forest RMSE 934 : 0.05492589 

nnet 934 : -0.3555224 
nnet mean 934 : -0.4256471 
nnet RMSE 934 : 0.1560551 


s: 935 
logit 935 : -0.4497741 
logit mean 935 : -0.4265810 
logit RMSE 935 : 0.067469 

boosting 935 : -0.3176906 
boosting mean 935 : -0.5054306 
boosting RMSE 935 : 0.1620149 

forest 935 : -0.3614168 
forest mean 935 : -0.3815128 
forest RMSE 935 : 0.05491101 

nnet 935 : -0.4318408 
nnet mean 935 : -0.4256537 
nnet RMSE 935 : 0.1559751 


s: 936 
logit 936 : -0.4531805 
logit mean 936 : -0.4266094 
logit RMSE 936 : 0.06745535 

boosting 936 : -0.5377665 
boosting mean 936 : -0.5054651 
boosting RMSE 936 : 0.1619909 

forest 936 : -0.4028865 
forest mean 936 : -0.3815357 
forest RMSE 936 : 0.05488175 

nnet 936 : -0.4640755 
nnet mean 936 : -0.4256948 
nnet RMSE 936 : 0.1559059 


s: 937 
logit 937 : -0.395351 
logit mean 937 : -0.426576 
logit RMSE 937 : 0.06741952 

boosting 937 : -0.4328285 
boosting mean 937 : -0.5053876 
boosting RMSE 937 : 0.161908 

forest 937 : -0.3047206 
forest mean 937 : -0.3814537 
forest RMSE 937 : 0.0549407 

nnet 937 : -0.5378091 
nnet mean 937 : -0.4258144 
nnet RMSE 937 : 0.1558877 


s: 938 
logit 938 : -0.4015741 
logit mean 938 : -0.4265494 
logit RMSE 938 : 0.06738359 

boosting 938 : -0.3827142 
boosting mean 938 : -0.5052568 
boosting RMSE 938 : 0.1618227 

forest 938 : -0.3864192 
forest mean 938 : -0.381459 
forest RMSE 938 : 0.05491319 

nnet 938 : -0.4733588 
nnet mean 938 : -0.4258651 
nnet RMSE 938 : 0.1558230 


s: 939 
logit 939 : -0.4700459 
logit mean 939 : -0.4265957 
logit RMSE 939 : 0.06738648 

boosting 939 : -0.4396611 
boosting mean 939 : -0.505187 
boosting RMSE 939 : 0.1617417 

forest 939 : -0.4922729 
forest mean 939 : -0.381577 
forest RMSE 939 : 0.05496649 

nnet 939 : -0.6335647 
nnet mean 939 : -0.4260863 
nnet RMSE 939 : 0.1559264 


s: 940 
logit 940 : -0.3808829 
logit mean 940 : -0.4265471 
logit RMSE 940 : 0.06735351 

boosting 940 : -0.3299803 
boosting mean 940 : -0.5050006 
boosting RMSE 940 : 0.1616717 

forest 940 : -0.3090156 
forest mean 940 : -0.3814998 
forest RMSE 940 : 0.05501734 

nnet 940 : -0.3419395 
nnet mean 940 : -0.4259968 
nnet RMSE 940 : 0.1558549 


s: 941 
logit 941 : -0.3692857 
logit mean 941 : -0.4264862 
logit RMSE 941 : 0.06732516 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 941 : -0.3674993 
boosting mean 941 : -0.5048545 
boosting RMSE 941 : 0.1615893 

forest 941 : -0.3348467 
forest mean 941 : -0.3814502 
forest RMSE 941 : 0.0550291 

nnet 941 : -0.3744346 
nnet mean 941 : -0.425942 
nnet RMSE 941 : 0.1557743 


s: 942 
logit 942 : -0.3968522 
logit mean 942 : -0.4264547 
logit RMSE 942 : 0.0672895 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 942 : -0.4786656 
boosting mean 942 : -0.5048267 
boosting RMSE 942 : 0.1615238 

forest 942 : -0.3512074 
forest mean 942 : -0.3814181 
forest RMSE 942 : 0.05502285 

nnet 942 : -0.5269923 
nnet mean 942 : -0.4260493 
nnet RMSE 942 : 0.1557466 


s: 943 
logit 943 : -0.4834405 
logit mean 943 : -0.4265152 
logit RMSE 943 : 0.06730867 

boosting 943 : -0.5283926 
boosting mean 943 : -0.5048516 
boosting RMSE 943 : 0.1614923 

forest 943 : -0.3625437 
forest mean 943 : -0.3813981 
forest RMSE 943 : 0.0550072 

nnet 943 : -0.5832109 
nnet mean 943 : -0.4262159 
nnet RMSE 943 : 0.1557783 


s: 944 
logit 944 : -0.4529987 
logit mean 944 : -0.4265432 
logit RMSE 944 : 0.06729513 

boosting 944 : -0.508308 
boosting mean 944 : -0.5048553 
boosting RMSE 944 : 0.1614452 

forest 944 : -0.351096 
forest mean 944 : -0.381366 
forest RMSE 944 : 0.05500109 

nnet 944 : -0.412949 
nnet mean 944 : -0.4262019 
nnet RMSE 944 : 0.1556963 


s: 945 
logit 945 : -0.5048576 
logit mean 945 : -0.4266261 
logit RMSE 945 : 0.06734595 

boosting 945 : -0.5988685 
boosting mean 945 : -0.5049548 
boosting RMSE 945 : 0.1614894 

forest 945 : -0.3819999 
forest mean 945 : -0.3813667 
forest RMSE 945 : 0.0549751 

nnet 945 : -0.1990338 
nnet mean 945 : -0.4259615 
nnet RMSE 945 : 0.1557512 


s: 946 
logit 946 : -0.3994023 
logit mean 946 : -0.4265973 
logit RMSE 946 : 0.06731035 

boosting 946 : -0.5121541 
boosting mean 946 : -0.5049624 
boosting RMSE 946 : 0.1614452 

forest 946 : -0.3732230 
forest mean 946 : -0.3813581 
forest RMSE 946 : 0.05495293 

nnet 946 : -0.4892761 
nnet mean 946 : -0.4260284 
nnet RMSE 946 : 0.1556959 


s: 947 
logit 947 : -0.3632674 
logit mean 947 : -0.4265304 
logit RMSE 947 : 0.06728539 

boosting 947 : -0.4820563 
boosting mean 947 : -0.5049382 
boosting RMSE 947 : 0.1613820 

forest 947 : -0.3489486 
forest mean 947 : -0.3813238 
forest RMSE 947 : 0.05494896 

nnet 947 : -0.4027509 
nnet mean 947 : -0.4260038 
nnet RMSE 947 : 0.1556137 


s: 948 
logit 948 : -0.3178942 
logit mean 948 : -0.4264158 
logit RMSE 948 : 0.06730274 

boosting 948 : -0.3538583 
boosting mean 948 : -0.5047788 
boosting RMSE 948 : 0.1613038 

forest 948 : -0.2901371 
forest mean 948 : -0.3812276 
forest RMSE 948 : 0.05503576 

nnet 948 : -0.3671982 
nnet mean 948 : -0.4259418 
nnet RMSE 948 : 0.1555352 


s: 949 
logit 949 : -0.4443465 
logit mean 949 : -0.4264347 
logit RMSE 949 : 0.06728267 

boosting 949 : -0.3517915 
boosting mean 949 : -0.5046176 
boosting RMSE 949 : 0.1612264 

forest 949 : -0.4295283 
forest mean 949 : -0.3812785 
forest RMSE 949 : 0.0550151 

nnet 949 : -0.4401162 
nnet mean 949 : -0.4259567 
nnet RMSE 949 : 0.1554587 


s: 950 
logit 950 : -0.3272802 
logit mean 950 : -0.4263304 
logit RMSE 950 : 0.06728863 

boosting 950 : -0.4991373 
boosting mean 950 : -0.5046119 
boosting RMSE 950 : 0.1611736 

forest 950 : -0.4377066 
forest mean 950 : -0.3813379 
forest RMSE 950 : 0.05499975 

nnet 950 : -0.680475 
nnet mean 950 : -0.4262247 
nnet RMSE 950 : 0.1556431 


s: 951 
logit 951 : -0.394262 
logit mean 951 : -0.4262967 
logit RMSE 951 : 0.0672535 

boosting 951 : -0.5592635 
boosting mean 951 : -0.5046693 
boosting RMSE 951 : 0.1611716 

forest 951 : -0.4739374 
forest mean 951 : -0.3814353 
forest RMSE 951 : 0.05502309 

nnet 951 : -0.5232454 
nnet mean 951 : -0.4263267 
nnet RMSE 951 : 0.1556126 


s: 952 
logit 952 : -0.4884598 
logit mean 952 : -0.4263619 
logit RMSE 952 : 0.06727928 

boosting 952 : -0.7415607 
boosting mean 952 : -0.5049182 
boosting RMSE 952 : 0.1614669 

forest 952 : -0.4053546 
forest mean 952 : -0.3814604 
forest RMSE 952 : 0.05499445 

nnet 952 : -0.3617867 
nnet mean 952 : -0.4262589 
nnet RMSE 952 : 0.1555358 


s: 953 
logit 953 : -0.3613531 
logit mean 953 : -0.4262937 
logit RMSE 953 : 0.06725562 

boosting 953 : -0.4475983 
boosting mean 953 : -0.504858 
boosting RMSE 953 : 0.1613895 

forest 953 : -0.3015503 
forest mean 953 : -0.3813766 
forest RMSE 953 : 0.05505803 

nnet 953 : -0.2492603 
nnet mean 953 : -0.4260732 
nnet RMSE 953 : 0.1555308 


s: 954 
logit 954 : -0.3265571 
logit mean 954 : -0.4261892 
logit RMSE 954 : 0.06726241 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 954 : -0.4053913 
boosting mean 954 : -0.5047538 
boosting RMSE 954 : 0.1613050 

forest 954 : -0.3433533 
forest mean 954 : -0.3813367 
forest RMSE 954 : 0.05505972 

nnet 954 : -0.4189856 
nnet mean 954 : -0.4260657 
nnet RMSE 954 : 0.1554505 


s: 955 
logit 955 : -0.5016787 
logit mean 955 : -0.4262682 
logit RMSE 955 : 0.06730765 

boosting 955 : -0.6523026 
boosting mean 955 : -0.5049083 
boosting RMSE 955 : 0.1614271 

forest 955 : -0.3437748 
forest mean 955 : -0.3812974 
forest RMSE 955 : 0.05506095 

nnet 955 : -0.3929744 
nnet mean 955 : -0.4260311 
nnet RMSE 955 : 0.1553692 


s: 956 
logit 956 : -0.4198168 
logit mean 956 : -0.4262615 
logit RMSE 956 : 0.06727549 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 956 : -0.3135909 
boosting mean 956 : -0.5047081 
boosting RMSE 956 : 0.1613668 

forest 956 : -0.3029501 
forest mean 956 : -0.3812154 
forest RMSE 956 : 0.05512159 

nnet 956 : -0.4905662 
nnet mean 956 : -0.4260986 
nnet RMSE 956 : 0.1553156 


s: 957 
logit 957 : -0.4305024 
logit mean 957 : -0.4262659 
logit RMSE 957 : 0.06724756 

boosting 957 : -0.2662376 
boosting mean 957 : -0.504459 
boosting RMSE 957 : 0.1613405 

forest 957 : -0.3879116 
forest mean 957 : -0.3812224 
forest RMSE 957 : 0.05509417 

nnet 957 : -0.4781441 
nnet mean 957 : -0.426153 
nnet RMSE 957 : 0.1552550 


s: 958 
logit 958 : -0.4200116 
logit mean 958 : -0.4262594 
logit RMSE 958 : 0.06721556 

boosting 958 : -0.4548398 
boosting mean 958 : -0.5044072 
boosting RMSE 958 : 0.1612660 

forest 958 : -0.3767283 
forest mean 958 : -0.3812177 
forest RMSE 958 : 0.05507054 

nnet 958 : -0.4662786 
nnet mean 958 : -0.4261949 
nnet RMSE 958 : 0.1551887 


s: 959 
logit 959 : -0.4308656 
logit mean 959 : -0.4262642 
logit RMSE 959 : 0.0671879 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 959 : -0.6520003 
boosting mean 959 : -0.5045611 
boosting RMSE 959 : 0.1613872 

forest 959 : -0.3551517 
forest mean 959 : -0.3811906 
forest RMSE 959 : 0.05506087 

nnet 959 : -0.4815658 
nnet mean 959 : -0.4262526 
nnet RMSE 959 : 0.1551301 


s: 960 
logit 960 : -0.5237332 
logit mean 960 : -0.4263657 
logit RMSE 960 : 0.06727154 

boosting 960 : -0.5542902 
boosting mean 960 : -0.5046129 
boosting RMSE 960 : 0.1613799 

forest 960 : -0.4293554 
forest mean 960 : -0.3812407 
forest RMSE 960 : 0.05504034 

nnet 960 : -0.4401254 
nnet mean 960 : -0.426267 
nnet RMSE 960 : 0.1550547 


s: 961 
logit 961 : -0.4064764 
logit mean 961 : -0.426345 
logit RMSE 961 : 0.06723685 

boosting 961 : -0.4727007 
boosting mean 961 : -0.5045797 
boosting RMSE 961 : 0.161313 

forest 961 : -0.3920358 
forest mean 961 : -0.381252 
forest RMSE 961 : 0.05501229 

nnet 961 : -0.4887593 
nnet mean 961 : -0.4263321 
nnet RMSE 961 : 0.1550005 


s: 962 
logit 962 : -0.2515893 
logit mean 962 : -0.4261634 
logit RMSE 962 : 0.06737203 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 962 : -0.2380113 
boosting mean 962 : -0.5043026 
boosting RMSE 962 : 0.1613137 

forest 962 : -0.3322338 
forest mean 962 : -0.381201 
forest RMSE 962 : 0.05502709 

nnet 962 : -0.2414992 
nnet mean 962 : -0.4261399 
nnet RMSE 962 : 0.1550041 


s: 963 
logit 963 : -0.5358632 
logit mean 963 : -0.4262773 
logit RMSE 963 : 0.06747922 

boosting 963 : -0.9200233 
boosting mean 963 : -0.5047343 
boosting RMSE 963 : 0.1620984 

forest 963 : -0.3780012 
forest mean 963 : -0.3811977 
forest RMSE 963 : 0.05500308 

nnet 963 : -0.7572666 
nnet mean 963 : -0.4264838 
nnet RMSE 963 : 0.1553508 


s: 964 
logit 964 : -0.4900144 
logit mean 964 : -0.4263434 
logit RMSE 964 : 0.0675065 

boosting 964 : -0.4968184 
boosting mean 964 : -0.504726 
boosting RMSE 964 : 0.1620443 

forest 964 : -0.4356628 
forest mean 964 : -0.3812542 
forest RMSE 964 : 0.05498654 

nnet 964 : -0.5479701 
nnet mean 964 : -0.4266098 
nnet RMSE 964 : 0.1553434 


s: 965 
logit 965 : -0.4105697 
logit mean 965 : -0.4263271 
logit RMSE 965 : 0.06747237 

boosting 965 : -0.4438723 
boosting mean 965 : -0.504663 
boosting RMSE 965 : 0.1619665 

forest 965 : -0.3590535 
forest mean 965 : -0.3812312 
forest RMSE 965 : 0.05497384 

nnet 965 : -0.3712088 
nnet mean 965 : -0.4265524 
nnet RMSE 965 : 0.1552656 


s: 966 
logit 966 : -0.5273025 
logit mean 966 : -0.4264316 
logit RMSE 966 : 0.0675617 

boosting 966 : -0.5341544 
boosting mean 966 : -0.5046935 
boosting RMSE 966 : 0.1619402 

forest 966 : -0.4439527 
forest mean 966 : -0.3812961 
forest RMSE 966 : 0.05496358 

nnet 966 : -0.3713501 
nnet mean 966 : -0.4264953 
nnet RMSE 966 : 0.1551880 


s: 967 
logit 967 : -0.3475507 
logit mean 967 : -0.42635 
logit RMSE 967 : 0.06754782 

boosting 967 : -0.877416 
boosting mean 967 : -0.505079 
boosting RMSE 967 : 0.1625829 

forest 967 : -0.4348941 
forest mean 967 : -0.3813515 
forest RMSE 967 : 0.05494661 

nnet 967 : -0.5189506 
nnet mean 967 : -0.4265909 
nnet RMSE 967 : 0.1551549 


s: 968 
logit 968 : -0.5218922 
logit mean 968 : -0.4264487 
logit RMSE 968 : 0.0676265 

boosting 968 : -0.4702366 
boosting mean 968 : -0.505043 
boosting RMSE 968 : 0.1625146 

forest 968 : -0.3059706 
forest mean 968 : -0.3812737 
forest RMSE 968 : 0.05500132 

nnet 968 : -0.1467296 
nnet mean 968 : -0.4263018 
nnet RMSE 968 : 0.1552882 


s: 969 
logit 969 : -0.4234108 
logit mean 969 : -0.4264456 
logit RMSE 969 : 0.06759578 

boosting 969 : -0.6218566 
boosting mean 969 : -0.5051635 
boosting RMSE 969 : 0.162587 

forest 969 : -0.369181 
forest mean 969 : -0.3812612 
forest RMSE 969 : 0.05498184 

nnet 969 : -0.4467036 
nnet mean 969 : -0.4263228 
nnet RMSE 969 : 0.1552153 


s: 970 
logit 970 : -0.3761412 
logit mean 970 : -0.4263937 
logit RMSE 970 : 0.06756527 

boosting 970 : -0.6432719 
boosting mean 970 : -0.5053059 
boosting RMSE 970 : 0.1626908 

forest 970 : -0.3412645 
forest mean 970 : -0.3812200 
forest RMSE 970 : 0.05498585 

nnet 970 : -0.4193119 
nnet mean 970 : -0.4263156 
nnet RMSE 970 : 0.1551365 


s: 971 
logit 971 : -0.4761615 
logit mean 971 : -0.426445 
logit RMSE 971 : 0.06757469 

boosting 971 : -0.4995411 
boosting mean 971 : -0.5053 
boosting RMSE 971 : 0.1626384 

forest 971 : -0.419428 
forest mean 971 : -0.3812593 
forest RMSE 971 : 0.05496106 

nnet 971 : -0.3376487 
nnet mean 971 : -0.4262243 
nnet RMSE 971 : 0.1550695 


s: 972 
logit 972 : -0.4880003 
logit mean 972 : -0.4265083 
logit RMSE 972 : 0.06759888 

boosting 972 : -0.7182022 
boosting mean 972 : -0.505519 
boosting RMSE 972 : 0.1628748 

forest 972 : -0.3700761 
forest mean 972 : -0.3812478 
forest RMSE 972 : 0.05494117 

nnet 972 : -0.3101258 
nnet mean 972 : -0.4261048 
nnet RMSE 972 : 0.1550165 


s: 973 
logit 973 : -0.4288196 
logit mean 973 : -0.4265107 
logit RMSE 973 : 0.06757045 

boosting 973 : -0.3878312 
boosting mean 973 : -0.505398 
boosting RMSE 973 : 0.1627915 

forest 973 : -0.3624284 
forest mean 973 : -0.3812285 
forest RMSE 973 : 0.05492613 

nnet 973 : -0.1521770 
nnet mean 973 : -0.4258233 
nnet RMSE 973 : 0.1551404 


s: 974 
logit 974 : -0.4067906 
logit mean 974 : -0.4264904 
logit RMSE 974 : 0.0675361 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 974 : -0.5327915 
boosting mean 974 : -0.5054262 
boosting RMSE 974 : 0.1627636 

forest 974 : -0.3489684 
forest mean 974 : -0.3811953 
forest RMSE 974 : 0.05492228 

nnet 974 : -0.5565758 
nnet mean 974 : -0.4259575 
nnet RMSE 974 : 0.1551419 


s: 975 
logit 975 : -0.4558372 
logit mean 975 : -0.4265205 
logit RMSE 975 : 0.06752514 

boosting 975 : -0.4566241 
boosting mean 975 : -0.5053761 
boosting RMSE 975 : 0.1626902 

forest 975 : -0.4074609 
forest mean 975 : -0.3812223 
forest RMSE 975 : 0.05489462 

nnet 975 : -0.4693466 
nnet mean 975 : -0.426002 
nnet RMSE 975 : 0.1550782 


s: 976 
logit 976 : -0.5399357 
logit mean 976 : -0.4266367 
logit RMSE 976 : 0.06763901 

boosting 976 : -0.4614917 
boosting mean 976 : -0.5053311 
boosting RMSE 976 : 0.1626187 

forest 976 : -0.431627 
forest mean 976 : -0.3812739 
forest RMSE 976 : 0.05487583 
Increasing memory because of ties: allocating a matrix of size 3 times 200000 doubles.
I would be faster with the ties=FALSE option.
Warning in MatchLoopCfast(N = s1$N, xvars = Kx, All = s1$All, M = s1$M,  :
  Increasing memory because of ties.  I would be faster with the ties=FALSE option.
Increasing memory because of ties: allocating a matrix of size 3 times 300000 doubles.
I would be faster with the ties=FALSE option.
Warning in MatchLoopCfast(N = s1$N, xvars = Kx, All = s1$All, M = s1$M,  :
  Increasing memory because of ties.  I would be faster with the ties=FALSE option.

nnet 976 : -0.2453890 
nnet mean 976 : -0.425817 
nnet RMSE 976 : 0.1550778 


s: 977 
logit 977 : -0.3993788 
logit mean 977 : -0.4266088 
logit RMSE 977 : 0.06760439 

boosting 977 : -0.3771347 
boosting mean 977 : -0.5051999 
boosting RMSE 977 : 0.1625371 

forest 977 : -0.2939239 
forest mean 977 : -0.3811845 
forest RMSE 977 : 0.05495263 

nnet 977 : -0.3197004 
nnet mean 977 : -0.4257084 
nnet RMSE 977 : 0.1550197 


s: 978 
logit 978 : -0.3382456 
logit mean 978 : -0.4265185 
logit RMSE 978 : 0.06759867 

boosting 978 : -0.4494863 
boosting mean 978 : -0.505143 
boosting RMSE 978 : 0.1624617 

forest 978 : -0.4188363 
forest mean 978 : -0.381223 
forest RMSE 978 : 0.05492783 

nnet 978 : -0.4262467 
nnet mean 978 : -0.4257089 
nnet RMSE 978 : 0.1549427 


s: 979 
logit 979 : -0.4693761 
logit mean 979 : -0.4265623 
logit RMSE 979 : 0.06760051 

boosting 979 : -0.3267672 
boosting mean 979 : -0.5049608 
boosting RMSE 979 : 0.1623956 

forest 979 : -0.2842304 
forest mean 979 : -0.3811239 
forest RMSE 979 : 0.05502432 

nnet 979 : -0.1123722 
nnet mean 979 : -0.4253889 
nnet RMSE 979 : 0.1551361 


s: 980 
logit 980 : -0.3248663 
logit mean 980 : -0.4264585 
logit RMSE 980 : 0.06760862 

boosting 980 : -0.7074428 
boosting mean 980 : -0.5051674 
boosting RMSE 980 : 0.1626096 

forest 980 : -0.3840989 
forest mean 980 : -0.381127 
forest RMSE 980 : 0.05499858 

nnet 980 : -0.3714861 
nnet mean 980 : -0.4253339 
nnet RMSE 980 : 0.1550596 


s: 981 
logit 981 : -0.4171698 
logit mean 981 : -0.426449 
logit RMSE 981 : 0.06757638 

boosting 981 : -0.5480353 
boosting mean 981 : -0.5052111 
boosting RMSE 981 : 0.1625954 

forest 981 : -0.4451412 
forest mean 981 : -0.3811922 
forest RMSE 981 : 0.05498943 

nnet 981 : -0.4510909 
nnet mean 981 : -0.4253601 
nnet RMSE 981 : 0.1549891 


s: 982 
logit 982 : -0.3496547 
logit mean 982 : -0.4263708 
logit RMSE 982 : 0.06756107 

boosting 982 : -0.4373744 
boosting mean 982 : -0.505142 
boosting RMSE 982 : 0.1625169 

forest 982 : -0.4175808 
forest mean 982 : -0.3812293 
forest RMSE 982 : 0.05496429 

nnet 982 : -0.2813187 
nnet mean 982 : -0.4252134 
nnet RMSE 982 : 0.1549565 


s: 983 
logit 983 : -0.4373437 
logit mean 983 : -0.426382 
logit RMSE 983 : 0.0675372 

boosting 983 : -0.4247157 
boosting mean 983 : -0.5050602 
boosting RMSE 983 : 0.1624362 

forest 983 : -0.3567558 
forest mean 983 : -0.3812044 
forest RMSE 983 : 0.05495364 

nnet 983 : -0.398574 
nnet mean 983 : -0.4251863 
nnet RMSE 983 : 0.1548777 


s: 984 
logit 984 : -0.3742519 
logit mean 984 : -0.426329 
logit RMSE 984 : 0.06750786 

boosting 984 : -0.3189991 
boosting mean 984 : -0.5048711 
boosting RMSE 984 : 0.1623741 

forest 984 : -0.4613397 
forest mean 984 : -0.3812858 
forest RMSE 984 : 0.0549605 

nnet 984 : -0.4281996 
nnet mean 984 : -0.4251894 
nnet RMSE 984 : 0.1548016 


s: 985 
logit 985 : -0.3931399 
logit mean 985 : -0.4262953 
logit RMSE 985 : 0.06747394 

boosting 985 : -0.6248047 
boosting mean 985 : -0.5049928 
boosting RMSE 985 : 0.1624497 

forest 985 : -0.3494213 
forest mean 985 : -0.3812535 
forest RMSE 985 : 0.05495623 

nnet 985 : -0.672413 
nnet mean 985 : -0.4254404 
nnet RMSE 985 : 0.1549662 


s: 986 
logit 986 : -0.2854755 
logit mean 986 : -0.4261525 
logit RMSE 986 : 0.06753826 

boosting 986 : -0.233768 
boosting mean 986 : -0.5047178 
boosting RMSE 986 : 0.1624536 

forest 986 : -0.3443832 
forest mean 986 : -0.3812161 
forest RMSE 986 : 0.05495691 

nnet 986 : -0.5276433 
nnet mean 986 : -0.425544 
nnet RMSE 986 : 0.1549410 


s: 987 
logit 987 : -0.4854861 
logit mean 987 : -0.4262126 
logit RMSE 987 : 0.06755886 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 987 : -0.3842447 
boosting mean 987 : -0.5045957 
boosting RMSE 987 : 0.1623720 

forest 987 : -0.3111073 
forest mean 987 : -0.3811451 
forest RMSE 987 : 0.05500189 

nnet 987 : -0.2621028 
nnet mean 987 : -0.4253784 
nnet RMSE 987 : 0.1549246 


s: 988 
logit 988 : -0.3847912 
logit mean 988 : -0.4261707 
logit RMSE 988 : 0.0675264 

boosting 988 : -0.1550559 
boosting mean 988 : -0.5042419 
boosting RMSE 988 : 0.1624768 

forest 988 : -0.3257266 
forest mean 988 : -0.3810890 
forest RMSE 988 : 0.0550248 

nnet 988 : -0.004796146 
nnet mean 988 : -0.4249527 
nnet RMSE 988 : 0.1553558 


s: 989 
logit 989 : -0.4095625 
logit mean 989 : -0.4261539 
logit RMSE 989 : 0.06749293 

boosting 989 : -0.5732658 
boosting mean 989 : -0.5043117 
boosting RMSE 989 : 0.1624881 

forest 989 : -0.4542942 
forest mean 989 : -0.381163 
forest RMSE 989 : 0.05502407 

nnet 989 : -0.2931347 
nnet mean 989 : -0.4248195 
nnet RMSE 989 : 0.1553144 


s: 990 
logit 990 : -0.4393931 
logit mean 990 : -0.4261673 
logit RMSE 990 : 0.06747046 

boosting 990 : -0.5386177 
boosting mean 990 : -0.5043464 
boosting RMSE 990 : 0.1624657 

forest 990 : -0.3658157 
forest mean 990 : -0.3811475 
forest RMSE 990 : 0.055007 

nnet 990 : -0.5101066 
nnet mean 990 : -0.4249056 
nnet RMSE 990 : 0.1552754 


s: 991 
logit 991 : -0.4895703 
logit mean 991 : -0.4262312 
logit RMSE 991 : 0.0674964 

boosting 991 : -0.5487535 
boosting mean 991 : -0.5043912 
boosting RMSE 991 : 0.1624525 

forest 991 : -0.3404144 
forest mean 991 : -0.3811064 
forest RMSE 991 : 0.05501182 

nnet 991 : -0.2238384 
nnet mean 991 : -0.4247027 
nnet RMSE 991 : 0.1552979 


s: 992 
logit 992 : -0.3896655 
logit mean 992 : -0.4261944 
logit RMSE 992 : 0.06746317 

boosting 992 : -0.3012654 
boosting mean 992 : -0.5041864 
boosting RMSE 992 : 0.1624009 

forest 992 : -0.3875496 
forest mean 992 : -0.3811129 
forest RMSE 992 : 0.0549855 

nnet 992 : -0.3440218 
nnet mean 992 : -0.4246214 
nnet RMSE 992 : 0.1552298 


s: 993 
logit 993 : -0.3898436 
logit mean 993 : -0.4261578 
logit RMSE 993 : 0.06742997 

boosting 993 : -0.3359070 
boosting mean 993 : -0.5040169 
boosting RMSE 993 : 0.1623318 

forest 993 : -0.3674201 
forest mean 993 : -0.3810991 
forest RMSE 993 : 0.05496753 

nnet 993 : -0.4298869 
nnet mean 993 : -0.4246267 
nnet RMSE 993 : 0.1551545 


s: 994 
logit 994 : -0.3075502 
logit mean 994 : -0.4260384 
logit RMSE 994 : 0.0674598 

boosting 994 : -0.2646222 
boosting mean 994 : -0.5037761 
boosting RMSE 994 : 0.1623069 

forest 994 : -0.4120385 
forest mean 994 : -0.3811302 
forest RMSE 994 : 0.0549412 

nnet 994 : -0.3143241 
nnet mean 994 : -0.4245157 
nnet RMSE 994 : 0.1551002 


s: 995 
logit 995 : -0.3496304 
logit mean 995 : -0.4259617 
logit RMSE 995 : 0.0674448 

boosting 995 : -0.6655478 
boosting mean 995 : -0.5039387 
boosting RMSE 995 : 0.1624436 

forest 995 : -0.3173649 
forest mean 995 : -0.3810661 
forest RMSE 995 : 0.05497604 

nnet 995 : -0.4902533 
nnet mean 995 : -0.4245818 
nnet RMSE 995 : 0.1550487 


s: 996 
logit 996 : -0.4487221 
logit mean 996 : -0.4259845 
logit RMSE 996 : 0.0674286 
Warning in ps(z.a ~ w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8 + w9 + w10, data = sdta,  :
  Optimal number of iterations is close to the specified n.trees. n.trees is likely set too small and better balance might be obtainable by setting n.trees to be larger.

boosting 996 : -0.3862745 
boosting mean 996 : -0.5038206 
boosting RMSE 996 : 0.1623627 

forest 996 : -0.4726534 
forest mean 996 : -0.3811581 
forest RMSE 996 : 0.05499664 

nnet 996 : -0.2044012 
nnet mean 996 : -0.4243607 
nnet RMSE 996 : 0.1550947 


s: 997 
logit 997 : -0.4937944 
logit mean 997 : -0.4260525 
logit RMSE 997 : 0.06746021 

boosting 997 : -0.4282927 
boosting mean 997 : -0.5037448 
boosting RMSE 997 : 0.1622837 

forest 997 : -0.2948035 
forest mean 997 : -0.3810715 
forest RMSE 997 : 0.05506992 

nnet 997 : -0.4612107 
nnet mean 997 : -0.4243977 
nnet RMSE 997 : 0.1550290 


s: 998 
logit 998 : -0.4270472 
logit mean 998 : -0.4260535 
logit RMSE 998 : 0.06743184 

boosting 998 : -0.3423446 
boosting mean 998 : -0.5035831 
boosting RMSE 998 : 0.1622126 

forest 998 : -0.4379739 
forest mean 998 : -0.3811285 
forest RMSE 998 : 0.05505545 

nnet 998 : -0.3571864 
nnet mean 998 : -0.4243303 
nnet RMSE 998 : 0.1549573 


s: 999 
logit 999 : -0.458109 
logit mean 999 : -0.4260856 
logit RMSE 999 : 0.06742316 

boosting 999 : -0.4976043 
boosting mean 999 : -0.5035771 
boosting RMSE 999 : 0.1621608 

forest 999 : -0.362484 
forest mean 999 : -0.3811098 
forest RMSE 999 : 0.05504068 

nnet 999 : -0.605075 
nnet mean 999 : -0.4245113 
nnet RMSE 999 : 0.1550155 


s: 1000 
logit 1000 : -0.3911321 
logit mean 1000 : -0.4260506 
logit RMSE 1000 : 0.06739002 

boosting 1000 : -0.5166655 
boosting mean 1000 : -0.5035902 
boosting RMSE 1000 : 0.1621217 

forest 1000 : -0.3849873 
forest mean 1000 : -0.3811137 
forest RMSE 1000 : 0.0550152 

nnet 1000 : -0.6474338 
nnet mean 1000 : -0.4247342 
nnet RMSE 1000 : 0.1551355 
> 
> 
> rm(sdta)
> save.image("RData.sims.D.nobs1000",compress="bzip2")
> 
> proc.time()
    user   system  elapsed 
46124.59    16.68 46537.21 
